Improve tts with codex extra high

engine/core/duplex_pipeline.py

@@ -49,6 +49,10 @@ class DuplexPipeline:
                   Barge-in Detection → Interrupt
     """
 
+    _SENTENCE_END_CHARS = frozenset({"。", "！", "？", ".", "!", "?", "\n"})
+    _SENTENCE_TRAILING_CHARS = frozenset({"。", "！", "？", ".", "!", "?", "…", "~", "～", "\n"})
+    _SENTENCE_CLOSERS = frozenset({'"', "'", "”", "’", ")", "]", "}", "）", "】", "」", "』", "》"})
+    
     def __init__(
         self,
         transport: BaseTransport,
@@ -499,8 +503,9 @@ class DuplexPipeline:
             
             # Sentence buffer for streaming TTS
             sentence_buffer = ""
-            sentence_ends = {'，', '。', '！', '？', '\n'}
+            pending_punctuation = ""
             first_audio_sent = False
+            spoken_sentence_count = 0
             
             # Stream LLM response and TTS sentence by sentence
             async for text_chunk in self.llm_service.generate_stream(messages):
@@ -521,19 +526,25 @@ class DuplexPipeline:
                 })
                 
                 # Check for sentence completion - synthesize immediately for low latency
-                while any(end in sentence_buffer for end in sentence_ends):
+                while True:
-                    # Find first sentence end
+                    split_result = self._extract_tts_sentence(sentence_buffer, force=False)
-                    min_idx = len(sentence_buffer)
+                    if not split_result:
-                    for end in sentence_ends:
+                        break
-                        idx = sentence_buffer.find(end)
+                    sentence, sentence_buffer = split_result
-                        if idx != -1 and idx < min_idx:
+                    if not sentence:
-                            min_idx = idx
+                        continue
 
-                    if min_idx < len(sentence_buffer):
+                    sentence = f"{pending_punctuation}{sentence}".strip()
-                        sentence = sentence_buffer[:min_idx + 1].strip()
+                    pending_punctuation = ""
-                        sentence_buffer = sentence_buffer[min_idx + 1:]
+                    if not sentence:
+                        continue
 
-                        if sentence and not self._interrupt_event.is_set():
+                    # Avoid synthesizing punctuation-only fragments (e.g. standalone "!")
+                    if not self._has_spoken_content(sentence):
+                        pending_punctuation = sentence
+                        continue
+
+                    if not self._interrupt_event.is_set():
                         # Send track start on first audio
                         if not first_audio_sent:
                             await self.transport.send_event({
@@ -544,10 +555,14 @@ class DuplexPipeline:
                             })
                             first_audio_sent = True
 
-                            # Synthesize and send this sentence immediately
+                        # Keep very short fade-in for non-first sentence to preserve consonant attack.
-                            await self._speak_sentence(sentence)
+                        fade_in_ms = 2 if spoken_sentence_count == 0 else 1
-                    else:
+                        await self._speak_sentence(
-                        break
+                            sentence,
+                            fade_in_ms=fade_in_ms,
+                            fade_out_ms=8,
+                        )
+                        spoken_sentence_count += 1
             
             # Send final LLM response event
             if full_response and not self._interrupt_event.is_set():
@@ -560,7 +575,8 @@ class DuplexPipeline:
                 })
             
             # Speak any remaining text
-            if sentence_buffer.strip() and not self._interrupt_event.is_set():
+            remaining_text = f"{pending_punctuation}{sentence_buffer}".strip()
+            if remaining_text and self._has_spoken_content(remaining_text) and not self._interrupt_event.is_set():
                 if not first_audio_sent:
                     await self.transport.send_event({
                         **ev(
@@ -569,7 +585,12 @@ class DuplexPipeline:
                         )
                     })
                     first_audio_sent = True
-                await self._speak_sentence(sentence_buffer.strip())
+                fade_in_ms = 2 if spoken_sentence_count == 0 else 1
+                await self._speak_sentence(
+                    remaining_text,
+                    fade_in_ms=fade_in_ms,
+                    fade_out_ms=8,
+                )
             
             # Send track end
             if first_audio_sent:
@@ -598,12 +619,53 @@ class DuplexPipeline:
             self._barge_in_speech_frames = 0
             self._barge_in_silence_frames = 0
     
-    async def _speak_sentence(self, text: str) -> None:
+    def _extract_tts_sentence(self, text_buffer: str, force: bool = False) -> Optional[tuple[str, str]]:
+        """
+        Extract one TTS sentence from the buffer.
+
+        Consecutive sentence terminators are grouped together to avoid creating
+        punctuation-only fragments such as a standalone "!" after "?". By
+        default, trailing terminator at buffer end is held for more context.
+        """
+        if not text_buffer:
+            return None
+
+        split_idx = -1
+        for idx, char in enumerate(text_buffer):
+            if char in self._SENTENCE_END_CHARS:
+                split_idx = idx
+                break
+
+        if split_idx == -1:
+            return None
+
+        end_idx = split_idx + 1
+        while end_idx < len(text_buffer) and text_buffer[end_idx] in self._SENTENCE_TRAILING_CHARS:
+            end_idx += 1
+
+        # Include trailing quote/bracket closers in the same segment.
+        while end_idx < len(text_buffer) and text_buffer[end_idx] in self._SENTENCE_CLOSERS:
+            end_idx += 1
+
+        if not force and end_idx >= len(text_buffer):
+            return None
+
+        sentence = text_buffer[:end_idx].strip()
+        remainder = text_buffer[end_idx:]
+        return sentence, remainder
+
+    def _has_spoken_content(self, text: str) -> bool:
+        """Check whether text contains pronounceable content (not punctuation-only)."""
+        return any(char.isalnum() for char in text)
+
+    async def _speak_sentence(self, text: str, fade_in_ms: int = 2, fade_out_ms: int = 8) -> None:
         """
         Synthesize and send a single sentence.
         
         Args:
             text: Sentence to speak
+            fade_in_ms: Fade-in duration for sentence start chunks
+            fade_out_ms: Fade-out duration for sentence end chunks
         """
         if not text.strip() or self._interrupt_event.is_set():
             return
@@ -640,7 +702,8 @@ class DuplexPipeline:
                     sample_rate=chunk.sample_rate,
                     fade_in=is_first_chunk,
                     fade_out=bool(chunk.is_final),
-                    fade_ms=8,
+                    fade_in_ms=fade_in_ms,
+                    fade_out_ms=fade_out_ms,
                 )
                 is_first_chunk = False
 
@@ -656,7 +719,8 @@ class DuplexPipeline:
         sample_rate: int,
         fade_in: bool = False,
         fade_out: bool = False,
-        fade_ms: int = 8,
+        fade_in_ms: int = 2,
+        fade_out_ms: int = 8,
     ) -> bytes:
         """Apply short edge fades to reduce click/pop at sentence boundaries."""
         if not pcm_bytes or (not fade_in and not fade_out):
@@ -667,13 +731,14 @@ class DuplexPipeline:
             if samples.size == 0:
                 return pcm_bytes
 
-            fade_samples = int(sample_rate * (fade_ms / 1000.0))
-            fade_samples = max(1, min(fade_samples, samples.size))
-
             if fade_in:
-                samples[:fade_samples] *= np.linspace(0.0, 1.0, fade_samples, endpoint=True)
+                fade_in_samples = int(sample_rate * (fade_in_ms / 1000.0))
+                fade_in_samples = max(1, min(fade_in_samples, samples.size))
+                samples[:fade_in_samples] *= np.linspace(0.0, 1.0, fade_in_samples, endpoint=True)
             if fade_out:
-                samples[-fade_samples:] *= np.linspace(1.0, 0.0, fade_samples, endpoint=True)
+                fade_out_samples = int(sample_rate * (fade_out_ms / 1000.0))
+                fade_out_samples = max(1, min(fade_out_samples, samples.size))
+                samples[-fade_out_samples:] *= np.linspace(1.0, 0.0, fade_out_samples, endpoint=True)
 
             return np.clip(samples, -32768, 32767).astype("<i2").tobytes()
         except Exception:

engine/examples/web_client.html

@@ -400,6 +400,7 @@
       let interimAiText = "";
 
       const targetSampleRate = 16000;
+      const playbackStopRampSec = 0.008;
 
       function logLine(type, text, data) {
         const time = new Date().toLocaleTimeString();
@@ -456,10 +457,18 @@
 
       function stopPlayback() {
         discardAudio = true;
-        playbackTime = audioCtx ? audioCtx.currentTime : 0;
+        const now = audioCtx ? audioCtx.currentTime : 0;
-        playbackSources.forEach((s) => {
+        playbackTime = now;
+        playbackSources.forEach((node) => {
           try {
-            s.stop();
+            if (audioCtx && node.gainNode && node.source) {
+              node.gainNode.gain.cancelScheduledValues(now);
+              node.gainNode.gain.setValueAtTime(node.gainNode.gain.value || 1, now);
+              node.gainNode.gain.linearRampToValueAtTime(0, now + playbackStopRampSec);
+              node.source.stop(now + playbackStopRampSec + 0.002);
+            } else if (node.source) {
+              node.source.stop();
+            }
           } catch (err) {}
         });
         playbackSources = [];
@@ -527,14 +536,18 @@
         const buffer = audioCtx.createBuffer(1, float32.length, targetSampleRate);
         buffer.copyToChannel(float32, 0);
         const source = audioCtx.createBufferSource();
+        const gainNode = audioCtx.createGain();
         source.buffer = buffer;
-        source.connect(playbackDest);
+        source.connect(gainNode);
+        gainNode.connect(playbackDest);
         const startTime = Math.max(audioCtx.currentTime + 0.02, playbackTime);
+        gainNode.gain.setValueAtTime(1, startTime);
         source.start(startTime);
         playbackTime = startTime + buffer.duration;
-        playbackSources.push(source);
+        const playbackNode = { source, gainNode };
+        playbackSources.push(playbackNode);
         source.onended = () => {
-          playbackSources = playbackSources.filter((s) => s !== source);
+          playbackSources = playbackSources.filter((s) => s !== playbackNode);
         };
       }
 

engine/services/siliconflow_tts.py

@@ -134,6 +134,7 @@ class SiliconFlowTTSService(BaseTTSService):
                 # Stream audio chunks
                 chunk_size = self.sample_rate * 2 // 10  # 100ms chunks
                 buffer = b""
+                pending_chunk = None
                 
                 async for chunk in response.content.iter_any():
                     if self._cancel_event.is_set():
@@ -147,13 +148,33 @@ class SiliconFlowTTSService(BaseTTSService):
                         audio_chunk = buffer[:chunk_size]
                         buffer = buffer[chunk_size:]
 
+                        # Keep one full chunk buffered so we can always tag the true
+                        # last full chunk as final when stream length is an exact multiple.
+                        if pending_chunk is not None:
                             yield TTSChunk(
-                            audio=audio_chunk,
+                                audio=pending_chunk,
                                 sample_rate=self.sample_rate,
                                 is_final=False
                             )
+                        pending_chunk = audio_chunk
+                
+                # Flush pending chunk(s) and remaining tail.
+                if pending_chunk is not None:
+                    if buffer:
+                        yield TTSChunk(
+                            audio=pending_chunk,
+                            sample_rate=self.sample_rate,
+                            is_final=False
+                        )
+                        pending_chunk = None
+                    else:
+                        yield TTSChunk(
+                            audio=pending_chunk,
+                            sample_rate=self.sample_rate,
+                            is_final=True
+                        )
+                        pending_chunk = None
 
-                # Yield remaining buffer
                 if buffer:
                     yield TTSChunk(
                         audio=buffer,
@@ -182,7 +203,7 @@ class StreamingTTSAdapter:
     """
     
     # Sentence delimiters
-    SENTENCE_ENDS = {'。', '！', '？', '\n'}
+    SENTENCE_ENDS = {'。', '！', '？', '.', '!', '?', '\n'}
     
     def __init__(self, tts_service: BaseTTSService, transport, session_id: str):
         self.tts_service = tts_service
@@ -205,15 +226,24 @@ class StreamingTTSAdapter:
         self._buffer += text_chunk
         
         # Check for sentence completion
+        while True:
+            split_idx = -1
             for i, char in enumerate(self._buffer):
                 if char in self.SENTENCE_ENDS:
-                # Found sentence end, synthesize up to this point
+                    split_idx = i
-                sentence = self._buffer[:i+1].strip()
-                self._buffer = self._buffer[i+1:]
-                
-                if sentence:
-                    await self._speak_sentence(sentence)
                     break
+            if split_idx < 0:
+                break
+
+            end_idx = split_idx + 1
+            while end_idx < len(self._buffer) and self._buffer[end_idx] in self.SENTENCE_ENDS:
+                end_idx += 1
+
+            sentence = self._buffer[:end_idx].strip()
+            self._buffer = self._buffer[end_idx:]
+
+            if sentence and any(ch.isalnum() for ch in sentence):
+                await self._speak_sentence(sentence)
     
     async def flush(self) -> None:
         """Flush remaining buffer."""