Merge branch 'vad'

* vad:
[fix]: update web.
[fix]: whisper_full_with_state: input is too short - 990 ms < 1000 ms. consider padding the input audio with silence.
[fix]: to 1.5b
filter empty message
update zh-en prompt add limit
update code structures and some code
update prompts and words

config/hotwords.json

@@ -5,8 +5,23 @@
     "GO SAME": "GOSIM",
     "go same": "GOSIM",
     "GoSync": "GOSIM",
+    "Go Son": "GOSIM",
     "CSN": "CSDN",
     "CSDF": "CSDN",
     "CSTN": "CSDN",
-    "OpenAZI": "Open AGI"
+    "OpenAZI": "Open AGI",
+    "CSdn": "CSDN",
+    "DeepSeq": "DeepSeek",
+    "deep sig": "DeepSeek",
+    "deep sick": "DeepSeek",
+    "chat GBT": "ChatGPT",
+    "Deep sike": "DeepSeek",
+    "Deep sink": "DeepSeek",
+    "它跟face": "huggingface",
+    "拉么index": "LlamaIndex",
+    "lama index": "LlamaIndex",
+    "rug": "RAG",
+    "defive": "Dify",
+    "define": "Dify",
+    "open minus":"open manus"
 }

config/hotwords.txt

@@ -32,3 +32,6 @@ MoXIN
 Function
 Func
 Lava
+C++
+阿里
+pipeline

config/keywords.txt

@@ -1,4 +1,8 @@
 OpenAGI
 GOSIM
 Rust
-LLaMA Factory
+LLaMA Factory
+OPENGL
+GPU
+Web3
+DeepSeek

config/prompt.py

@@ -34,16 +34,24 @@ LLM_SYS_7B_PROMPT_EN = """
 """.format(keywords_mapping_string=keywords_mapping_string)
 
 LLM_SYS_7B_PROMPT_ZH = """
-你是一个中英文翻译专家，请将以下文本从中文翻译成英文，但保留所有英文专业术语、产品名称、代码片段和专有名词的原始英文形式。遇到英文专业术语或需要保留的内容时，请使用原始英文表达，不要翻译。
-翻译规则：
-1. 保留以下内容的原始英文形式，不翻译：
-   - 技术术语和专业词汇
-   - 产品名称、品牌名称
-   - 代码片段、函数名、变量名
-   - 专有名词、缩写和首字母缩略词
-2. 翻译其余内容时，请确保：
-   - 保持原文的段落结构
-   - 翻译内容符合中文表达习惯
-   - 保持专业性和准确性
-如遇到难以判断是否需要保留英文的情况，请优先保留原始英文形式。
+你是一位中英文翻译专家。请将以下中文文本翻译成英文，遵循以下要求：
+
+翻译要求：
+- 保留原文英文内容：以下内容请保持原始英文形式，不进行翻译或改写：
+- 技术术语与专业词汇
+- 产品名称、品牌名称
+- 代码片段、函数名、变量名
+- 专有名词、缩写、首字母缩略词（如 API、NLP、RAG 等）
+- 翻译符合英文表达习惯，流畅自然，不生硬直译。
+- 保持专业性与准确性，清晰传达原意。
+- 如遇原文表达模糊或逻辑不清的情况，允许适度调整语序或措辞，以增强英文表述的清晰度和逻辑性。
+
+注意：
+若难以确定某个词汇是否需要翻译，请优先保留原始英文形式。
+不需添加额外解释或注释，仅翻译正文内容。
+特别注意，翻译的内容只能包含英文，不能包含其他的语言。
+
 文本："""
+
+LLM_SYS_PROMPT_EN = LLM_SYS_7B_PROMPT_EN
+LLM_SYS_PROMPT_ZH =LLM_SYS_7B_PROMPT_ZH

frontend/assets/{index-a619a94d.js → index-4906844f.js}

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+`),X=new Blob([Y],{type:"text/plain"}),J=URL.createObjectURL(X),K=document.createElement("a");K.href=J,K.download="record.txt",document.body.appendChild(K),K.click(),document.body.removeChild(K),URL.revokeObjectURL(J)},H=oe(null),_=()=>{ot(()=>{H.value&&(H.value.scrollTop=H.value.scrollHeight+144)})};be(()=>[...w],()=>{_()},{deep:!0}),be(()=>T.value,()=>{_()});const B=oe(!1),N=()=>{B.value=!0},k=()=>{B.value=!1,F.value!=t.$state.vad&&(t.$state.vad=F.value,c.value&&y())},F=oe(.3),L=oe(!1),z=oe("trans-font-size-18"),j=oe(!0),q=Y=>{console.log("onFontSizeChange",Y.target.value),z.value=Y.target.value,t.$state.fs=Y.target.value};return(Y,X)=>{const J=xo("a-radio"),K=xo("a-radio-group"),ee=xo("a-switch"),Z=xo("a-button"),U=xo("a-popover"),Q=xo("a-select"),W=xo("a-popconfirm"),G=xo("a-card");return 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frontend/assets/{index-c1b225bf.css → index-54c9f9d3.css}

@@ -1 +1 @@
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438px)}.content-wrapper .content-box[data-v-c39ab0d6]{padding:24px;height:240px;background-color:#e8e8e8;border-radius:16px;width:50%;margin:48px auto;min-width:300px}.content-wrapper .video-box[data-v-c39ab0d6]{max-width:800px;min-width:320px;width:90vw;height:auto}
+html,body{width:100%;height:100%}input::-ms-clear,input::-ms-reveal{display:none}*,*:before,*:after{box-sizing:border-box}html{font-family:sans-serif;line-height:1.15;-webkit-text-size-adjust:100%;-ms-text-size-adjust:100%;-ms-overflow-style:scrollbar;-webkit-tap-highlight-color:rgba(0,0,0,0)}body{margin:0}[tabindex="-1"]:focus{outline:none}hr{box-sizing:content-box;height:0;overflow:visible}h1,h2,h3,h4,h5,h6{margin-top:0;margin-bottom:.5em;font-weight:500}p{margin-top:0;margin-bottom:1em}abbr[title],abbr[data-original-title]{-webkit-text-decoration:underline dotted;text-decoration:underline;text-decoration:underline dotted;border-bottom:0;cursor:help}address{margin-bottom:1em;font-style:normal;line-height:inherit}input[type=text],input[type=password],input[type=number],textarea{-webkit-appearance:none}ol,ul,dl{margin-top:0;margin-bottom:1em}ol ol,ul ul,ol ul,ul ol{margin-bottom:0}dt{font-weight:500}dd{margin-bottom:.5em;margin-left:0}blockquote{margin:0 0 1em}dfn{font-style:italic}b,strong{font-weight:bolder}small{font-size:80%}sub,sup{position:relative;font-size:75%;line-height:0;vertical-align:baseline}sub{bottom:-.25em}sup{top:-.5em}pre,code,kbd,samp{font-size:1em;font-family:SFMono-Regular,Consolas,Liberation Mono,Menlo,Courier,monospace}pre{margin-top:0;margin-bottom:1em;overflow:auto}figure{margin:0 0 1em}img{vertical-align:middle;border-style:none}a,area,button,[role=button],input:not([type=range]),label,select,summary,textarea{touch-action:manipulation}table{border-collapse:collapse}caption{padding-top:.75em;padding-bottom:.3em;text-align:left;caption-side:bottom}input,button,select,optgroup,textarea{margin:0;color:inherit;font-size:inherit;font-family:inherit;line-height:inherit}button,input{overflow:visible}button,select{text-transform:none}button,html [type=button],[type=reset],[type=submit]{-webkit-appearance:button}button::-moz-focus-inner,[type=button]::-moz-focus-inner,[type=reset]::-moz-focus-inner,[type=submit]::-moz-focus-inner{padding:0;border-style:none}input[type=radio],input[type=checkbox]{box-sizing:border-box;padding:0}input[type=date],input[type=time],input[type=datetime-local],input[type=month]{-webkit-appearance:listbox}textarea{overflow:auto;resize:vertical}fieldset{min-width:0;margin:0;padding:0;border:0}legend{display:block;width:100%;max-width:100%;margin-bottom:.5em;padding:0;color:inherit;font-size:1.5em;line-height:inherit;white-space:normal}progress{vertical-align:baseline}[type=number]::-webkit-inner-spin-button,[type=number]::-webkit-outer-spin-button{height:auto}[type=search]{outline-offset:-2px;-webkit-appearance:none}[type=search]::-webkit-search-cancel-button,[type=search]::-webkit-search-decoration{-webkit-appearance:none}::-webkit-file-upload-button{font:inherit;-webkit-appearance:button}output{display:inline-block}summary{display:list-item}template{display:none}[hidden]{display:none!important}mark{padding:.2em;background-color:#feffe6}:root{font-family:Inter,system-ui,Avenir,Helvetica,Arial,sans-serif;line-height:1.5;font-weight:400;color-scheme:light dark;color:#ffffffde;background-color:#242424;font-synthesis:none;text-rendering:optimizeLegibility;-webkit-font-smoothing:antialiased;-moz-osx-font-smoothing:grayscale;-webkit-text-size-adjust:100%}a{font-weight:500;color:#646cff;text-decoration:inherit}a:hover{color:#535bf2}body{margin:0;display:flex;place-items:center;min-width:320px;height:auto;min-height:auto;color:#333;background:#fff}h1{font-size:3.2em;line-height:1.1}button{border-radius:8px;border:1px solid transparent;padding:.6em 1.2em;font-size:1em;font-weight:500;font-family:inherit;background-color:#1a1a1a;cursor:pointer;transition:border-color .25s}.card{border-bottom:solid 2px lightgray;align-items:center;justify-content:center;margin-top:40px;display:flex;max-width:1024px;width:100%}.seg-title{margin:24px 0;font-size:20px;font-weight:500}.seg-co{width:1022px;text-align:left;border-left:solid 6px midnightblue;padding-left:8px;margin-left:2px;margin-top:36px;line-height:24px}#app{margin:0 auto;padding:0;text-align:center;width:100%}.ant-btn{padding:4px 12px}@media (prefers-color-scheme: light){:root{color:#213547;background-color:#fff}a:hover{color:#747bff}button{background-color:#f9f9f9}}.ant-card{background:#f5f6fa}.ant-card .ant-card-actions{background-color:#e8e8f8cc!important}.ant-popover{max-width:800px!important}.ant-form-item{background:transparent;margin-bottom:40px!important}.ant-form-item .ant-form-item-explain-error{color:#ff4d4f;text-align:left!important}.ant-form-item-label label{font-size:18px!important;color:#1a1a1a!important;font-weight:500!important}.ant-tooltip{max-width:1022px!important}.ant-page-header-heading{width:1022px!important}.highlight{background:ghostwhite}.content[data-v-178d5f9f]{background-color:#fff;max-width:1280px;min-height:720px;margin:0 auto;display:flex;flex-direction:column;align-items:center;justify-content:space-between}.not-found-wrapper[data-v-aef52a59]{height:calc(100vh - 104px)}.config-content[data-v-b118bb94]{width:420px;margin:12px}.config-content .config-block[data-v-b118bb94]{margin:12px;padding-bottom:12px}.view-wrapper[data-v-b118bb94]{width:100%;height:100%;background-color:#fff}.view-wrapper .wrapper-width-fixed[data-v-b118bb94]{width:1280px}.view-wrapper .wrapper-width-auto[data-v-b118bb94]{width:100vw}.view-wrapper .content-wrapper[data-v-b118bb94]{text-align:left;max-width:100vw;min-width:320px;margin-bottom:64px;min-height:calc(100vh - 438px)}.view-wrapper .content-wrapper .chat-box[data-v-b118bb94]{width:100%;height:54vh;border-radius:4px;padding:12px;color:#2e2f33;font-size:18px}.view-wrapper .content-wrapper .chat-box-placeholder[data-v-b118bb94]{width:100%;height:58vh;border-radius:4px;padding:12px;font-size:18px;color:#a4a6ac}.view-wrapper .content-wrapper .actions-box[data-v-b118bb94]{display:flex;align-items:center;justify-content:space-between;margin:0 24px;height:48px}.view-wrapper .content-wrapper .actions-box .left-actions[data-v-b118bb94]{display:flex;align-items:center;justify-content:space-between;width:332px}.view-wrapper .content-wrapper .actions-box .right-actions[data-v-b118bb94]{display:flex;align-items:center;justify-content:space-between;width:108px}.view-wrapper .content-wrapper .trans-list[data-v-b118bb94]{overflow-y:auto;width:100%;height:58vh;scrollbar-width:none;-ms-overflow-style:none}.view-wrapper .content-wrapper .trans-list[data-v-b118bb94]::-webkit-scrollbar{display:none}.view-wrapper .content-wrapper .trans-list .node[data-v-b118bb94]{margin-bottom:36px;width:100%!important;transition:all .3s ease}.view-wrapper .content-wrapper .trans-list .node .trans-time[data-v-b118bb94]{font-size:14px;color:#c4c6cc}.view-wrapper .content-wrapper .trans-list .node .trans-font-size-16[data-v-b118bb94]{font-size:16px}.view-wrapper .content-wrapper .trans-list .node .trans-font-size-18[data-v-b118bb94]{font-size:18px}.view-wrapper .content-wrapper .trans-list .node .trans-font-size-20[data-v-b118bb94]{font-size:20px}.view-wrapper .content-wrapper .trans-list .node .trans-font-size-22[data-v-b118bb94]{font-size:22px}.view-wrapper .content-wrapper .trans-list .node .trans-font-size-24[data-v-b118bb94]{font-size:24px}.view-wrapper .content-wrapper .trans-list .node .trans-src-lang[data-v-b118bb94]{color:#909299;font-weight:500}.view-wrapper .content-wrapper .trans-list .node .trans-dst-lang[data-v-b118bb94]{color:#2e2f33;font-weight:600}.view-wrapper .content-wrapper .trans-list .current_node[data-v-b118bb94]{background-color:#f0f1f7;padding:4px 8px}@keyframes highlight-b118bb94{0%{background-color:transparent}50%{background-color:#fff1ce80}to{background-color:transparent}}@keyframes slideIn-b118bb94{0%{opacity:0;transform:translateY(10px)}to{opacity:1;transform:translateY(0)}}.content-wrapper[data-v-c39ab0d6]{text-align:left;max-width:800px;min-width:320px;margin-bottom:64px;min-height:calc(100vh - 438px)}.content-wrapper .content-box[data-v-c39ab0d6]{padding:24px;height:240px;background-color:#e8e8e8;border-radius:16px;width:50%;margin:48px auto;min-width:300px}.content-wrapper .video-box[data-v-c39ab0d6]{max-width:800px;min-width:320px;width:90vw;height:auto}

frontend/index.html

@@ -5,8 +5,8 @@
     <link rel="icon" type="image/svg+xml" href="./favicon.ico" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" />
     <title>Translator</title>
-    <script type="module" crossorigin src="./assets/index-a619a94d.js"></script>
-    <link rel="stylesheet" href="./assets/index-c1b225bf.css">
+    <script type="module" crossorigin src="./assets/index-4906844f.js"></script>
+    <link rel="stylesheet" href="./assets/index-54c9f9d3.css">
   </head>
   <body>
     <div id="app"></div>

frontend/index2.html

@@ -1,169 +0,0 @@
-<!DOCTYPE html>
-<html lang="zh">
-<head>
-  <meta charset="UTF-8" />
-  <title>试试翻译</title>
-  <style>
-    body {
-      background-color: #f9f9fc;
-      font-family: -apple-system, BlinkMacSystemFont, "Segoe UI", Roboto, "Helvetica Neue", sans-serif;
-      margin: 0;
-      padding: 2rem;
-    }
-    .translation-box {
-      background: #f2f2f8;
-      border-radius: 12px;
-      padding: 1.5rem;
-      max-width: 800px;
-      margin: 0 auto;
-      min-height: 200px;
-    }
-    .entry {
-      margin-bottom: 1.5rem;
-    }
-    .timestamp {
-      font-size: 0.75rem;
-      color: #999;
-    }
-    .original {
-      font-size: 1rem;
-      color: #333;
-    }
-    .translation {
-      font-size: 1rem;
-      font-weight: bold;
-      color: #000;
-    }
-    .footer {
-      display: flex;
-      justify-content: space-between;
-      align-items: center;
-      margin-top: 2rem;
-    }
-    .lang-select {
-      background: white;
-      border-radius: 9999px;
-      padding: 0.4rem 1rem;
-      border: none;
-      font-size: 1rem;
-      box-shadow: 0 0 0 1px #ddd;
-    }
-    .record-button {
-      background-color: #1e40af;
-      color: white;
-      border: none;
-      padding: 0.6rem 1.2rem;
-      border-radius: 9999px;
-      font-size: 1rem;
-      cursor: pointer;
-    }
-  </style>
-</head>
-<body>
-  <div class="translation-box" id="translationBox">
-    <!-- 实时内容将插入这里 -->
-  </div>
-
-  <div class="footer">
-    <select class="lang-select">
-      <option>中文 » 英语</option>
-    </select>
-    <button class="record-button" onclick="startRecording()">🎤 录音</button>
-  </div>
-
-  <script>
-    let ws;
-    let mediaRecorder;
-
-    function formatTimestamp(ms) {
-      const sec = ms / 1000;
-      const min = Math.floor(sec / 60);
-      const s = (sec % 60).toFixed(1);
-      return `${String(min).padStart(2, '0')}:${s.padStart(4, '0')}`;
-    }
-
-    let lastSegId = null;  // 用于存储上一个 seg_id
-
-function addTranslation(result) {
-  const box = document.getElementById('translationBox');
-  
-  // 创建一个新的 div 来显示翻译
-  const entry = document.createElement('div');
-  entry.className = 'entry';
-  
-  console.log(result);
-
-  const start = formatTimestamp(result.bg);
-  const end = formatTimestamp(result.ed);
-  
-  // 判断是否是新的一行
-  if (result.seg_id === lastSegId) {
-    // 如果 seg_id 相同，更新该行内容
-    const existingEntry = box.querySelector(`.entry[data-seg-id="${result.seg_id}"]`);
-    if (existingEntry) {
-      const translationDiv = existingEntry.querySelector('.translation');
-      translationDiv.innerHTML = result.tranContent;
-    }
-  } else {
-    // 如果 seg_id 不同，表示是新的行，添加新行
-    entry.setAttribute('data-seg-id', result.seg_id);  // 设置 seg_id
-    entry.innerHTML = `
-      <div class="original">${result.context}</div>
-      <div class="translation">${result.tranContent}</div>
-    `;
-    box.appendChild(entry);
-  }
-
-  // 更新 lastSegId 以便下一次判断
-  lastSegId = result.seg_id;
-}
-
-
-    
-    async function startRecording() {
-      const stream = await navigator.mediaDevices.getUserMedia({ audio: true });
-      const audioContext = new AudioContext({ sampleRate: 16000 });
-      const source = audioContext.createMediaStreamSource(stream);
-      const processor = audioContext.createScriptProcessor(4096, 1, 1);
-
-      const wsUrl = "ws://localhost:9191/ws?from=zh&to=en";
-      ws = new WebSocket(wsUrl);
-
-      ws.binaryType = "arraybuffer";
-
-      ws.onopen = () => {
-        console.log("WebSocket opened");
-        source.connect(processor);
-        processor.connect(audioContext.destination);
-
-        processor.onaudioprocess = (e) => {
-          const input = e.inputBuffer.getChannelData(0);
-          const buffer = new Int16Array(input.length);
-          for (let i = 0; i < input.length; i++) {
-            buffer[i] = Math.max(-1, Math.min(1, input[i])) * 0x7FFF;
-          }
-          ws.send(buffer);
-        };
-      };
-
-      ws.onmessage = (event) => {
-        try {
-          const msg = JSON.parse(event.data);
-          if (msg.result) {
-            addTranslation(msg.result);
-          }
-        } catch (e) {
-          console.error("Parse error:", e);
-        }
-      };
-
-      ws.onerror = (e) => console.error("WebSocket error:", e);
-      ws.onclose = () => {
-        console.log("WebSocket closed");
-        processor.disconnect();
-        source.disconnect();
-      };
-    }
-  </script>
-</body>
-</html>

main.py

@@ -1,6 +1,5 @@
 from fastapi import FastAPI, WebSocket, WebSocketDisconnect
-from urllib.parse import urlparse, parse_qsl
-from transcribe.whisper_llm_serve import WhisperTranscriptionService
+from transcribe.serve import WhisperTranscriptionService
 from uuid import uuid1
 from logging import getLogger
 import numpy as np

transcribe/pipelines/pipe_vad.py

@@ -72,7 +72,7 @@ class VadPipe(BasePipe):
                 logging.debug(" 🫷Speech ended, capturing audio up to frame: {}".format(rel_end_frame))
             else:
                 self._status = 'END'
-                target_audio = source_audio[rel_start_frame:rel_end_frame]
+                target_audio = source_audio[max(rel_start_frame-100, 0):rel_end_frame]
                 logging.debug(" 🔄 Speech segment captured from frame {} to frame {}".format(rel_start_frame, rel_end_frame))
                 # logging.debug("❌ No valid speech segment detected, setting status to END")
         else:

transcribe/{whisper_llm_serve.py → serve.py}

@@ -7,9 +7,9 @@ import asyncio
 import numpy as np
 import config
 import collections
-from api_model import TransResult, Message, DebugResult
+from api_model import TransResult, Message
 
-from .utils import log_block, save_to_wave, TestDataWriter, filter_words
+from .utils import log_block, start_thread, get_text_separator, filter_words
 from .translatepipes import TranslatePipes
 
 from transcribe.pipelines import MetaItem
@@ -18,26 +18,12 @@ from transcribe.pipelines import MetaItem
 logger = getLogger("TranscriptionService")
 
 
-def _get_text_separator(language: str) -> str:
-    """根据语言返回适当的文本分隔符"""
-    return "" if language == "zh" else " "
-
-
-def _start_thread(target_function) -> threading.Thread:
-    """启动守护线程执行指定函数"""
-    thread = threading.Thread(target=target_function)
-    thread.daemon = True
-    thread.start()
-    return thread
-
 
 class WhisperTranscriptionService:
     """
     Whisper语音转录服务类，处理音频流转录和翻译
     """
 
-    SERVER_READY = "SERVER_READY"
-    DISCONNECT = "DISCONNECT"
 
     def __init__(self, websocket, pipe: TranslatePipes, language=None, dst_lang=None, client_uid=None):
         print('>>>>>>>>>>>>>>>> init service >>>>>>>>>>>>>>>>>>>>>>')
@@ -47,52 +33,37 @@ class WhisperTranscriptionService:
         self.client_uid = client_uid
         # 转录结果稳定性管理
         self.websocket = websocket
-        self._translate_pipe = pipe
-
+        self.translate_pipe = pipe
         # 音频处理相关
         self.sample_rate = config.SAMPLE_RATE
 
         self.lock = threading.Lock()
         # 文本分隔符，根据语言设置
-        self.text_separator = _get_text_separator(language)
+        self.text_separator = get_text_separator(language)
         self.loop = asyncio.get_event_loop()
         #  原始音频队列
-        self._frame_queue = queue.Queue()
+        self.frame_queue = queue.Queue()
         #  音频队列缓冲区
         self.frames_np = np.array([], dtype=np.float32)
+        #  音频开始的时间点 用于约束最小断句时间
         self.frames_np_start_timestamp = None
         #  完整音频队列
         self.full_segments_queue = collections.deque()
         # 启动处理线程
-        self._translate_thread_stop = threading.Event()
-        self._frame_processing_thread_stop = threading.Event()
-
-        self.translate_thread = _start_thread(self._transcription_processing_loop)
-        self.frame_processing_thread = _start_thread(self._read_frame_processing_loop)
+        self._stop = threading.Event()
+        self.translate_thread = start_thread(self._transcription_processing_loop)
+        self.frame_processing_thread = start_thread(self._read_frame_processing_loop)
+        # 行号
         self.row_number = 0
-        # for test
-        self._transcribe_time_cost = 0.
-        self._translate_time_cost = 0.
 
-        if config.SAVE_DATA_SAVE:
-            self._save_task_stop = threading.Event()
-            self._save_queue = queue.Queue()
-            self._save_thread = _start_thread(self.save_data_loop)
-
-
-    def save_data_loop(self):
-        writer = TestDataWriter()
-        while not self._save_task_stop.is_set():
-            test_data = self._save_queue.get()
-            writer.write(test_data)  # Save test_data to CSV
 
     def add_frames(self, frame_np: np.ndarray) -> None:
         """添加音频帧到处理队列"""
-        self._frame_queue.put(frame_np)
+        self.frame_queue.put(frame_np)
 
     def _apply_voice_activity_detection(self, frame_np:np.array):
         """应用语音活动检测来优化音频缓冲区"""
-        processed_audio = self._translate_pipe.voice_detect(frame_np.tobytes())
+        processed_audio = self.translate_pipe.voice_detect(frame_np.tobytes())
         speech_audio =  np.frombuffer(processed_audio.audio, dtype=np.float32)
         speech_status = processed_audio.speech_status
         return speech_audio, speech_status
@@ -100,9 +71,9 @@ class WhisperTranscriptionService:
 
     def _read_frame_processing_loop(self) -> None:
         """从队列获取音频帧并合并到缓冲区"""
-        while not self._frame_processing_thread_stop.is_set():
+        while not self._stop.is_set():
             try:
-                frame_np = self._frame_queue.get(timeout=0.1)
+                frame_np = self.frame_queue.get(timeout=0.1)
                 frame_np, speech_status = self._apply_voice_activity_detection(frame_np)
 
                 if frame_np is None:
@@ -121,7 +92,7 @@ class WhisperTranscriptionService:
                         self.full_segments_queue.appendleft(audio_array) # 根据时间是否满足三秒长度 来整合音频块
                         self.frames_np_start_timestamp = time.time()
                         self.frames_np = np.array([], dtype=np.float32)
-                    
+
                     # 音频结束信号的时候 整合当前缓冲区
                     #   START -- END -- START -- END 通常
                     #   START -- END -- END  end块带有音频信息的通常是4096内断的一个短音
@@ -134,7 +105,7 @@ class WhisperTranscriptionService:
                             self.frames_np = np.array([], dtype=np.float32)
                         else:
                             logger.debug(f"🥳 当前时间与上一句的时间差: {time_diff:.2f}s,继续保留在缓冲区")
-                    
+
             except queue.Empty:
                 pass
 
@@ -142,8 +113,8 @@ class WhisperTranscriptionService:
         """主转录处理循环"""
         frame_epoch = 1
 
-        while not self._translate_thread_stop.is_set():
-      
+        while not self._stop.is_set():
+
             if len(self.frames_np) ==0:
                 time.sleep(0.1)
                 continue
@@ -155,11 +126,21 @@ class WhisperTranscriptionService:
                 else:
                     audio_buffer = self.frames_np[:int(frame_epoch * 1.5 * self.sample_rate)].copy()# 获取 1.5s * epoch 个音频长度
                     partial = True
-            
+
             if len(audio_buffer) < int(self.sample_rate):
-                silence_audio = np.zeros(self.sample_rate, dtype=np.float32)
-                silence_audio[-len(audio_buffer):] = audio_buffer
+                # Add a small buffer (e.g., 10ms worth of samples) to be safe
+                padding_samples = int(self.sample_rate * 0.01) # e.g., 160 samples for 10ms at 16kHz
+                target_length = self.sample_rate + padding_samples
+                silence_audio = np.zeros(target_length, dtype=np.float32)
+                # Ensure we don't try to copy more data than exists if audio_buffer is very short
+                copy_length = min(len(audio_buffer), target_length)
+                silence_audio[-copy_length:] = audio_buffer[-copy_length:] # Copy from the end of audio_buffer
                 audio_buffer = silence_audio
+            elif len(audio_buffer) > self.sample_rate * config.MAX_SPEECH_DURATION_S:
+                 # If buffer is too long even without padding, truncate it (optional, depends on desired behavior)
+                 # This case might already be handled elsewhere, but good to consider
+                 audio_buffer = audio_buffer[:int(self.sample_rate * config.MAX_SPEECH_DURATION_S)]
+
 
             logger.debug(f"audio buffer size: {len(audio_buffer) / self.sample_rate:.2f}s")
             meta_item = self._transcribe_audio(audio_buffer)
@@ -169,6 +150,8 @@ class WhisperTranscriptionService:
 
             if len(segments):
                 seg_text = self.text_separator.join(seg.text for seg in segments)
+                if not seg_text.strip(): # 过滤空字符
+                    continue
                 # 整行
                 if not partial:
                     translated_content = self._translate_text_large(seg_text)
@@ -187,54 +170,35 @@ class WhisperTranscriptionService:
                     partial=partial
                 )
                 self._send_result_to_client(result)
-    
-
 
     def _transcribe_audio(self, audio_buffer: np.ndarray)->MetaItem:
         """转录音频并返回转录片段"""
         log_block("Audio buffer length", f"{audio_buffer.shape[0]/self.sample_rate:.2f}", "s")
-        start_time = time.perf_counter()
-
-        result = self._translate_pipe.transcribe(audio_buffer.tobytes(), self.source_language)
-        segments = result.segments
-        time_diff = (time.perf_counter() - start_time)
-        logger.debug(f"📝 transcribe Segments: {segments} ")
-        log_block("📝 transcribe output", f"{self.text_separator.join(seg.text for seg in segments)}", "")
-        log_block("📝 transcribe time", f"{time_diff:.3f}", "s")
-        self._transcribe_time_cost = round(time_diff, 3)
+        result = self.translate_pipe.transcribe(audio_buffer.tobytes(), self.source_language)
+        log_block("📝 transcribe output", f"{self.text_separator.join(seg.text for seg in result.segments)}", "")
+
         return result
 
     def _translate_text(self, text: str) -> str:
         """将文本翻译为目标语言"""
         if not text.strip():
             return ""
-
         log_block("🐧 Translation input ", f"{text}")
-        start_time = time.perf_counter()
 
-        result = self._translate_pipe.translate(text, self.source_language, self.target_language)
+        result = self.translate_pipe.translate(text, self.source_language, self.target_language)
         translated_text = result.translate_content
-        time_diff = (time.perf_counter() - start_time)
-        log_block("🐧 Translation time ", f"{time_diff:.3f}", "s")
+
         log_block("🐧 Translation out ", f"{translated_text}")
-        self._translate_time_cost = round(time_diff, 3)
         return translated_text
 
     def _translate_text_large(self, text: str) -> str:
         """将文本翻译为目标语言"""
         if not text.strip():
             return ""
-
         log_block("Translation input", f"{text}")
-        start_time = time.perf_counter()
-
-        result = self._translate_pipe.translate_large(text, self.source_language, self.target_language)
+        result = self.translate_pipe.translate_large(text, self.source_language, self.target_language)
         translated_text = result.translate_content
-
-        time_diff = (time.perf_counter() - start_time)
-        log_block("Translation large model time ", f"{time_diff:.3f}", "s")
         log_block("Translation large model output", f"{translated_text}")
-        self._translate_time_cost = round(time_diff, 3)
         return translated_text
 
 
@@ -252,8 +216,5 @@ class WhisperTranscriptionService:
 
     def stop(self) -> None:
         """停止所有处理线程并清理资源"""
-        self._translate_thread_stop.set()
-        self._frame_processing_thread_stop.set()
-        if config.SAVE_DATA_SAVE:
-            self._save_task_stop.set()
+        self._stop.set()
         logger.info(f"Stopping transcription service for client: {self.client_uid}")

transcribe/translatepipes.py

@@ -1,5 +1,5 @@
-from transcribe.pipelines import WhisperPipe, MetaItem, WhisperChinese, Translate7BPipe, FunASRPipe, VadPipe, TranslatePipe
-
+from .pipelines import WhisperPipe, MetaItem, WhisperChinese, Translate7BPipe, FunASRPipe, VadPipe, TranslatePipe
+from .utils import timer
 
 class TranslatePipes:
     def __init__(self) -> None:
@@ -26,6 +26,7 @@ class TranslatePipes:
         for p in self._process:
             p.wait()
 
+    @timer(name="🐧 Translate")
     def translate(self, text, src_lang, dst_lang) -> MetaItem:
         item = MetaItem(
             transcribe_content=text,
@@ -34,6 +35,7 @@ class TranslatePipes:
         self._translate_pipe.input_queue.put(item)
         return self._translate_pipe.output_queue.get()
 
+    @timer(name="🐧 Translate-large")
     def translate_large(self, text, src_lang, dst_lang) -> MetaItem:
         item = MetaItem(
             transcribe_content=text,
@@ -47,6 +49,7 @@ class TranslatePipes:
             return self._funasr_pipe
         return self._whisper_pipe_en
 
+    @timer(name="📝 transcribe")
     def transcribe(self, audio_buffer: bytes, src_lang: str) -> MetaItem:
         transcription_model = self.get_transcription_model(src_lang)
         item = MetaItem(audio=audio_buffer, source_language=src_lang)

transcribe/utils.py

@@ -8,8 +8,9 @@ import config
 import csv
 import av
 import re
-import json
-
+from functools import wraps
+import time
+import threading
 # Compile regex patterns once outside the loop for better performance
 p_pattern = re.compile(r"(\s*\[.*?\])")
 p_start_pattern = re.compile(r"(\s*\[.*)")
@@ -178,6 +179,32 @@ def pcm_bytes_to_np_array(pcm_bytes: bytes, dtype=np.float32, channels=1):
         audio_np = audio_np.reshape(-1, channels)
     return audio_np
 
+def timer(name: str):
+    def decorator(func):
+        @wraps(func)
+        def wrapper(*args, **kwargs):
+            start_time = time.perf_counter()
+            result = func(*args, **kwargs)
+            end_time = time.perf_counter()
+            duration = end_time - start_time
+            log_block(f"{name} cost:", f"{duration:.2f} s")
+            return result
+        return wrapper
+    return decorator
+
+def get_text_separator(language: str) -> str:
+    """根据语言返回适当的文本分隔符"""
+    return "" if language == "zh" else " "
+
+
+def start_thread(target_function) -> threading.Thread:
+    """启动守护线程执行指定函数"""
+    thread = threading.Thread(target=target_function)
+    thread.daemon = True
+    thread.start()
+    return thread
+
+
 class TestDataWriter:
     def __init__(self, file_path='test_data.csv'):
         self.file_path = file_path