452 lines
14 KiB
Go
452 lines
14 KiB
Go
//go:build extra
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// +build extra
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package extra
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import (
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"bytes"
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"fmt"
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"gf-lt/models"
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"gf-lt/onnx"
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"log/slog"
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"os/exec"
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"strings"
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"sync"
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"time"
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"github.com/gopxl/beep/v2"
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"github.com/gopxl/beep/v2/speaker"
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"github.com/gopxl/beep/v2/wav"
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"github.com/neurosnap/sentences/english"
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"github.com/yalue/onnxruntime_go"
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)
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// KokoroONNXOrator implements Kokoro TTS using ONNX runtime
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type KokoroONNXOrator struct {
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logger *slog.Logger
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mu sync.Mutex
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session *onnxruntime_go.DynamicAdvancedSession
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phonemeMap map[string]int
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espeakCmd string
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voice string
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speed float32
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styleVector []float32
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currentStream *beep.Ctrl
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currentDone chan bool
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textBuffer strings.Builder
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interrupt bool
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modelLoaded bool
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modelPath string
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voicesPath string
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}
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// Phoneme to token ID mapping from Kokoro tokenizer.json
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var kokoroPhonemeMap = map[string]int{
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"$": 0, ";": 1, ":": 2, ",": 3, ".": 4, "!": 5, "?": 6, "—": 9, "…": 10, "\"": 11, "(": 12, ")": 13, "“": 14, "”": 15, " ": 16, "̃": 17, "ˢ": 18, "ˤ": 19, "˦": 20, "˨": 21, "ᾝ": 22, "⭧": 23,
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"A": 24, "I": 25, "O": 31, "Q": 33, "S": 35, "T": 36, "W": 39, "Y": 41, "ʲ": 42,
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"a": 43, "b": 44, "c": 45, "d": 46, "e": 47, "f": 48, "h": 50, "i": 51, "j": 52, "k": 53, "l": 54, "m": 55, "n": 56, "o": 57, "p": 58, "q": 59, "r": 60, "s": 61, "t": 62, "u": 63, "v": 64, "w": 65, "x": 66, "y": 67, "z": 68,
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"ɑ": 69, "ɐ": 70, "ɒ": 71, "æ": 72, "β": 75, "ɔ": 76, "ɕ": 77, "ç": 78, "ɖ": 80, "ð": 81, "˔": 82, "ə": 83, "ɚ": 85, "ɛ": 86, "ɜ": 87, "ɟ": 90, "ɡ": 92, "ɥ": 99, "ɨ": 101, "ɪ": 102, "ɝ": 103, "ɯ": 110, "ɰ": 111, "ŋ": 112, "ɳ": 113, "ɲ": 114, "ɴ": 115, "ø": 116, "ɸ": 118, "θ": 119, "œ": 120, "ɹ": 123, "ɾ": 125, "ɺ": 126, "ʁ": 128, "ɽ": 129, "ʂ": 130, "ʃ": 131, "ʈ": 132, "˧": 133, "ʊ": 135, "ʋ": 136, "ʌ": 138, "ɢ": 139, "ɣ": 140, "χ": 142, "ʎ": 143, "ʒ": 147, "ʔ": 148,
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"ˈ": 156, "ˌ": 157, "ː": 158, "̰": 162, "̊": 164, "↕": 169, "→": 171, "↗": 172, "↘": 173, "ᶻ": 177,
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}
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func (o *KokoroONNXOrator) ensureInitialized(modelPath string) error {
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o.logger.Debug("ensureInitialized called", "modelPath", modelPath)
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if o.modelLoaded {
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o.logger.Debug("model already loaded")
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return nil
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}
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o.mu.Lock()
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defer o.mu.Unlock()
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if o.modelLoaded {
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return nil
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}
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if modelPath == "" {
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o.logger.Error("modelPath is empty, cannot load ONNX model")
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return fmt.Errorf("modelPath is empty, set KokoroModelPath in config")
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}
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// Initialize ONNX runtime (shared with embedder)
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if err := onnx.Init(); err != nil {
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o.logger.Error("ONNX init failed", "error", err)
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return fmt.Errorf("ONNX init failed: %w", err)
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}
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if onnx.HasCUDASupport() {
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o.logger.Info("ONNX using CUDA")
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} else {
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o.logger.Info("ONNX using CPU fallback")
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}
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if o.phonemeMap == nil {
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o.phonemeMap = kokoroPhonemeMap
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}
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if o.espeakCmd == "" {
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o.espeakCmd = "espeak-ng"
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if _, err := exec.LookPath(o.espeakCmd); err != nil {
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o.espeakCmd = "espeak"
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if _, err := exec.LookPath(o.espeakCmd); err != nil {
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return fmt.Errorf("espeak-ng or espeak not found. Install with: sudo apt-get install espeak-ng")
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}
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}
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}
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o.logger.Info("using espeak command", "cmd", o.espeakCmd)
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// Load voice embedding if not already loaded
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if o.styleVector == nil {
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voiceName := o.voice
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if voiceName == "" {
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voiceName = "af_bella"
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}
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if o.voicesPath != "" {
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styleVec, err := onnx.LoadVoice(o.voicesPath, voiceName)
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if err != nil {
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o.logger.Warn("failed to load voice, using zeros", "error", err, "voice", voiceName)
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o.styleVector = make([]float32, 256)
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} else {
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// Shape is (510, 1, 256), we want the last 256 values (or first? let's use mean or just pick one)
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// Actually, let's average across all 510 to get a single 256-dim vector
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o.styleVector = make([]float32, 256)
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for i := 0; i < 256; i++ {
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var sum float32
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for j := 0; j < 510; j++ {
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sum += styleVec[j*256+i]
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}
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o.styleVector[i] = sum / 510.0
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}
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o.logger.Info("loaded voice embedding", "voice", voiceName)
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}
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} else {
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o.logger.Warn("no voices path configured, using zeros for style")
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o.styleVector = make([]float32, 256)
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}
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}
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opts, err := onnx.NewSessionOptions()
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if err != nil {
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return fmt.Errorf("failed to create session options: %w", err)
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}
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defer func() { _ = opts.Destroy() }()
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if onnx.HasCUDASupport() {
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o.logger.Info("session options created with CUDA")
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} else {
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o.logger.Info("session options created with CPU")
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}
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session, err := onnxruntime_go.NewDynamicAdvancedSession(
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modelPath,
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[]string{"input_ids", "style", "speed"},
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[]string{"waveform"},
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opts,
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)
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if err != nil {
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o.logger.Error("failed to create ONNX session", "error", err)
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return fmt.Errorf("failed to create ONNX session: %w", err)
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}
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o.session = session
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o.modelLoaded = true
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o.logger.Info("Kokoro ONNX model loaded successfully", "model", modelPath)
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return nil
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}
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func (o *KokoroONNXOrator) textToPhonemes(text string) (string, error) {
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o.logger.Debug("converting text to phonemes", "text", text)
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cmd := exec.Command(o.espeakCmd, "-x", "-q", text)
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output, err := cmd.Output()
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if err != nil {
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o.logger.Error("espeak failed", "error", err, "cmd", o.espeakCmd, "text", text)
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return "", fmt.Errorf("espeak failed: %w", err)
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}
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phonemeStr := strings.TrimSpace(string(output))
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o.logger.Debug("phonemes generated", "phonemes", phonemeStr)
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return phonemeStr, nil
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}
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func (o *KokoroONNXOrator) phonemesToTokens(phonemeStr string) ([]int, error) {
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o.logger.Debug("converting phonemes to tokens", "phonemes", phonemeStr)
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if phonemeStr == "" {
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o.logger.Error("empty phoneme string")
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return nil, fmt.Errorf("empty phoneme string")
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}
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// Iterate over each character in the phoneme string
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tokens := make([]int, 0)
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for _, ch := range phonemeStr {
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chStr := string(ch)
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if tokenID, ok := o.phonemeMap[chStr]; ok {
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tokens = append(tokens, tokenID)
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}
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}
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if len(tokens) == 0 {
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o.logger.Error("no phonemes mapped to tokens", "phonemeStr", phonemeStr)
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return nil, fmt.Errorf("no valid phonemes mapped to tokens")
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}
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o.logger.Debug("tokens generated", "count", len(tokens), "tokens", tokens)
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return tokens, nil
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}
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func (o *KokoroONNXOrator) generateAudio(text string) ([]float32, error) {
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o.logger.Debug("generateAudio called", "text", text, "speed", o.speed)
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if err := o.ensureInitialized(o.modelPath); err != nil {
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o.logger.Error("ensureInitialized failed", "error", err)
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return nil, err
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}
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phonemeStr, err := o.textToPhonemes(text)
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if err != nil {
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o.logger.Error("phoneme conversion failed", "error", err)
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return nil, fmt.Errorf("phoneme conversion failed: %w", err)
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}
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tokens, err := o.phonemesToTokens(phonemeStr)
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if err != nil {
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o.logger.Error("token conversion failed", "error", err)
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return nil, fmt.Errorf("token conversion failed: %w", err)
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}
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if len(tokens) > 510 {
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return nil, fmt.Errorf("text too long: %d tokens (max 510)", len(tokens))
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}
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tokens = append([]int{0}, tokens...)
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tokens = append(tokens, 0)
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o.logger.Debug("tokens prepared", "count", len(tokens))
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inputIDs := make([]int64, len(tokens))
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for i, t := range tokens {
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inputIDs[i] = int64(t)
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}
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inputTensor, err := onnxruntime_go.NewTensor[int64](
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onnxruntime_go.NewShape(1, int64(len(inputIDs))),
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inputIDs,
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)
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if err != nil {
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o.logger.Error("failed to create input tensor", "error", err)
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return nil, fmt.Errorf("failed to create input tensor: %w", err)
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}
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defer func() { _ = inputTensor.Destroy() }()
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o.logger.Debug("input tensor created", "shape", fmt.Sprintf("[1,%d]", len(inputIDs)))
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styleTensor, err := onnxruntime_go.NewTensor[float32](
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onnxruntime_go.NewShape(1, 256),
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o.styleVector,
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)
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if err != nil {
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o.logger.Error("failed to create style tensor", "error", err)
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return nil, fmt.Errorf("failed to create style tensor: %w", err)
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}
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defer func() { _ = styleTensor.Destroy() }()
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speedTensor, err := onnxruntime_go.NewTensor[float32](
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onnxruntime_go.NewShape(1),
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[]float32{o.speed},
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)
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if err != nil {
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o.logger.Error("failed to create speed tensor", "error", err)
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return nil, fmt.Errorf("failed to create speed tensor: %w", err)
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}
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defer func() { _ = speedTensor.Destroy() }()
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o.logger.Debug("speed tensor created", "speed", o.speed)
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outputTensor, err := onnxruntime_go.NewEmptyTensor[float32](
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onnxruntime_go.NewShape(1, 512),
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)
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if err != nil {
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o.logger.Error("failed to create output tensor", "error", err)
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return nil, fmt.Errorf("failed to create output tensor: %w", err)
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}
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defer func() { _ = outputTensor.Destroy() }()
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o.logger.Debug("output tensor created", "shape", "[1,512]")
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o.logger.Info("running ONNX inference", "input_len", len(inputIDs))
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err = o.session.Run(
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[]onnxruntime_go.Value{inputTensor, styleTensor, speedTensor},
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[]onnxruntime_go.Value{outputTensor},
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)
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if err != nil {
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o.logger.Error("ONNX inference failed", "error", err)
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return nil, fmt.Errorf("ONNX inference failed: %w", err)
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}
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o.logger.Debug("ONNX inference completed")
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audioData := outputTensor.GetData()
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if len(audioData) == 0 {
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o.logger.Error("empty audio output from ONNX")
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return nil, fmt.Errorf("empty audio output")
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}
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o.logger.Debug("audio generated", "samples", len(audioData))
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audio := make([]float32, len(audioData))
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copy(audio, audioData)
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return audio, nil
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}
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func (o *KokoroONNXOrator) Speak(text string) error {
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o.logger.Debug("KokoroONNX Speak called", "text_len", len(text))
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audio, err := o.generateAudio(text)
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if err != nil {
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o.logger.Error("audio generation failed", "error", err)
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return fmt.Errorf("audio generation failed: %w", err)
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}
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o.logger.Debug("audio ready for playback", "samples", len(audio))
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// Create streamer for encoding
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encodeStreamer := beep.StreamerFunc(func(samples [][2]float64) (n int, ok bool) {
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for i := range samples {
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if i >= len(audio) {
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return i, false
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}
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samples[i][0] = float64(audio[i])
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samples[i][1] = float64(audio[i])
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}
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return len(audio), true
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})
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buf := &seekableBuffer{new(bytes.Buffer)}
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err = wav.Encode(buf, encodeStreamer, beep.Format{
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SampleRate: 24000,
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NumChannels: 1,
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Precision: 2,
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})
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if err != nil {
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o.logger.Error("wav encoding failed", "error", err)
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return fmt.Errorf("wav encoding failed: %w", err)
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}
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o.logger.Debug("wav encoded", "size", buf.Len())
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decodedStreamer, format, err := wav.Decode(bytes.NewReader(buf.Bytes()))
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if err != nil {
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o.logger.Error("wav decode failed", "error", err)
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return fmt.Errorf("wav decode failed: %w", err)
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}
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defer decodedStreamer.Close()
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o.logger.Debug("wav decoded", "format", format)
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if err := speaker.Init(format.SampleRate, format.SampleRate.N(time.Second/10)); err != nil {
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o.logger.Error("speaker init failed", "error", err)
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return fmt.Errorf("speaker init failed: %w", err)
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}
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o.logger.Info("playing audio", "sampleRate", format.SampleRate, "channels", format.NumChannels)
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done := make(chan bool)
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o.mu.Lock()
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o.currentDone = done
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o.currentStream = &beep.Ctrl{Streamer: beep.Seq(decodedStreamer, beep.Callback(func() {
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o.logger.Debug("playback finished")
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o.mu.Lock()
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close(done)
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o.currentStream = nil
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o.currentDone = nil
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o.mu.Unlock()
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})), Paused: false}
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o.mu.Unlock()
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speaker.Play(o.currentStream)
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<-done
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o.logger.Debug("Speak completed")
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return nil
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}
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func (o *KokoroONNXOrator) Stop() {
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o.logger.Debug("stopping KokoroONNX orator")
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speaker.Lock()
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defer speaker.Unlock()
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o.mu.Lock()
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defer o.mu.Unlock()
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if o.currentStream != nil {
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o.currentStream.Streamer = nil
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}
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}
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func (o *KokoroONNXOrator) GetLogger() *slog.Logger {
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return o.logger
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}
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func (o *KokoroONNXOrator) stoproutine() {
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o.logger.Debug("KokoroONNX stoproutine started")
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for {
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<-TTSDoneChan
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o.logger.Debug("KokoroONNX got done signal")
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o.Stop()
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for len(TTSTextChan) > 0 {
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<-TTSTextChan
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}
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o.mu.Lock()
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o.textBuffer.Reset()
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if o.currentDone != nil {
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select {
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case o.currentDone <- true:
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default:
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}
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}
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o.interrupt = true
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o.mu.Unlock()
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o.logger.Debug("KokoroONNX stoproutine finished")
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}
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}
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func (o *KokoroONNXOrator) readroutine() {
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o.logger.Debug("KokoroONNX readroutine started")
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tokenizer, _ := english.NewSentenceTokenizer(nil)
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for {
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select {
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case chunk := <-TTSTextChan:
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o.logger.Debug("KokoroONNX received chunk", "chunk_len", len(chunk))
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o.mu.Lock()
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o.interrupt = false
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_, err := o.textBuffer.WriteString(chunk)
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if err != nil {
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o.logger.Warn("failed to write to buffer", "error", err)
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o.mu.Unlock()
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continue
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}
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text := o.textBuffer.String()
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sentences := tokenizer.Tokenize(text)
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o.logger.Debug("KokoroONNX tokenized", "total_sentences", len(sentences), "buffer", text)
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if len(sentences) <= 1 {
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o.logger.Debug("KokoroONNX not enough sentences, waiting")
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o.mu.Unlock()
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continue
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}
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completeSentences := sentences[:len(sentences)-1]
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remaining := sentences[len(sentences)-1].Text
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o.textBuffer.Reset()
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o.textBuffer.WriteString(remaining)
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o.logger.Debug("KokoroONNX processing sentences", "count", len(completeSentences))
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o.mu.Unlock()
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for _, sentence := range completeSentences {
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o.mu.Lock()
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interrupted := o.interrupt
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o.mu.Unlock()
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if interrupted {
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o.logger.Debug("KokoroONNX interrupted, exiting")
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return
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}
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cleanedText := models.CleanText(sentence.Text)
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if cleanedText == "" {
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continue
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}
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o.logger.Info("KokoroONNX speak", "text", cleanedText)
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if err := o.Speak(cleanedText); err != nil {
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o.logger.Error("KokoroONNX tts failed", "text", cleanedText, "error", err)
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}
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}
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case <-TTSFlushChan:
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o.logger.Debug("KokoroONNX flush signal")
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if len(TTSTextChan) > 0 {
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for chunk := range TTSTextChan {
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o.mu.Lock()
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_, err := o.textBuffer.WriteString(chunk)
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o.mu.Unlock()
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if err != nil {
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continue
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}
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if len(TTSTextChan) == 0 {
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break
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}
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}
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}
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o.mu.Lock()
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remaining := o.textBuffer.String()
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remaining = models.CleanText(remaining)
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o.textBuffer.Reset()
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o.mu.Unlock()
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if remaining == "" {
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continue
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}
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sentencesRem := tokenizer.Tokenize(remaining)
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for _, rs := range sentencesRem {
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o.mu.Lock()
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interrupt := o.interrupt
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o.mu.Unlock()
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if interrupt {
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break
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}
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if err := o.Speak(rs.Text); err != nil {
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o.logger.Error("tts failed", "text", rs.Text, "error", err)
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}
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}
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}
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}
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}
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