From 84551d59eb5ce2644313a76ac0103e05161fafaf Mon Sep 17 00:00:00 2001 From: DIng <1442618363@qq.com> Date: Sat, 3 Jan 2026 22:24:02 +0800 Subject: [PATCH] =?UTF-8?q?=E5=89=8D=E7=BD=AE=E5=94=A4=E9=86=92=E8=AF=8D?= =?UTF-8?q?=E8=AF=86=E5=88=AB=E4=BC=98=E5=8C=96?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- core/recorder.py | 136 +++++++++++++++++++++++++++++++++++------------ 1 file changed, 103 insertions(+), 33 deletions(-) diff --git a/core/recorder.py b/core/recorder.py index a6a56a2..f8a6a64 100644 --- a/core/recorder.py +++ b/core/recorder.py @@ -16,11 +16,68 @@ import tempfile import wave from core import fay_core from core import interact +# ===== 新增：用于前置唤醒词句首容错 ===== +import re +import unicodedata + # 启动时间 (秒) -_ATTACK = 0.2 +_ATTACK = 0.08 # ↓ 改小：让系统更早进入拾音，避免“唤醒词前半截被吃掉” # 释放时间 (秒) -_RELEASE = 0.7 +_RELEASE = 0.55 # ↓ 略微缩短，避免一句话被切成两段 + +# ===== 新增：前置唤醒词句首规范化与匹配 ===== +_PUNCS = "，。！？!?,.、:：；;“”\"'()（）[]【】<>《》-—…" # 常见中文标点 +_FILLER_PREFIX = ("嗯", "啊", "呃", "欸", "诶", "喂", "那个", "就是", "然后") # 常见句首语气词（ASR 很容易加） + +def _norm_head(s: str) -> str: + """只做句首容错：去不可见/空白/句首标点/句首语气词，不改变正文结构。""" + if not s: + return "" + s = unicodedata.normalize("NFKC", s).strip() + # 去掉开头空白 + s = re.sub(r"^\s+", "", s) + # 去掉开头标点（可重复） + s = re.sub(r"^[{}]+".format(re.escape(_PUNCS)), "", s) + + # 去掉句首常见语气词（允许多次叠加） + changed = True + while changed: + changed = False + for fp in _FILLER_PREFIX: + if s.startswith(fp): + s = s[len(fp):] + s = re.sub(r"^\s+", "", s) + s = re.sub(r"^[{}]+".format(re.escape(_PUNCS)), "", s) + changed = True + break + return s + +def _front_wake_match(text: str, wake_words): + """ + 前置唤醒词匹配（严格前置）： + - 唤醒词必须在规范化后的最前面 + - 不允许句中唤醒 + """ + t = _norm_head(text) + + for w in wake_words: + w = w.strip() + if not w: + continue + + # 允许：唤醒词后面紧跟空格/标点/语气助词 + # 例："小橄榄，帮我..." "小橄榄啊 帮我..." + if t.startswith(w): + rest = t[len(w):] # 去掉唤醒词，得到真正的问题 + # 去掉紧随其后的标点 / 空格 / 语气助词 + rest = rest.lstrip(" \t\r\n" + _PUNCS) + rest = re.sub(r"^(啊|呀|呢|吧|哈|哎|诶|欸)\s*", "", rest) + rest = rest.lstrip(" \t\r\n" + _PUNCS) + return True, w, rest + + return False, None, "" + class Recorder: @@ -141,35 +198,45 @@ class Recorder: self.timer.cancel() # 取消之前的计时器任务 self.timer = threading.Timer(60, self.reset_wakeup_status) # 重设计时器为60秒 self.timer.start() - - #前置唤醒词模式 - elif cfg.config['source']['wake_word_type'] == 'front': - wake_word = cfg.config['source']['wake_word'] - wake_word_list = wake_word.split(',') - wake_up = False - for word in wake_word_list: - if text.startswith(word): - wake_up_word = word - wake_up = True - break - if wake_up: + + # 前置唤醒词模式（严格前置，但句首做容错） + elif cfg.config['source']['wake_word_type'] == 'front': + # 读取配置的唤醒词（支持多个） + wake_word = cfg.config['source']['wake_word'] + wake_word_list = [w.strip() for w in wake_word.split(',') if w.strip()] + + matched, wake_up_word, question = _front_wake_match(text, wake_word_list) + + if matched: util.printInfo(1, self.username, "唤醒成功！") if wsa_server.get_web_instance().is_connected(self.username): - wsa_server.get_web_instance().add_cmd({"panelMsg": "唤醒成功！", "Username" : self.username , 'robot': f'http://{cfg.fay_url}:5000/robot/Listening.jpg'}) + wsa_server.get_web_instance().add_cmd({"panelMsg": "唤醒成功！", "Username": self.username, + 'robot': f'http://{cfg.fay_url}:5000/robot/Listening.jpg'}) if wsa_server.get_instance().is_connected(self.username): - content = {'Topic': 'Unreal', 'Data': {'Key': 'log', 'Value': "唤醒成功！"}, 'Username' : self.username, 'robot': f'http://{cfg.fay_url}:5000/robot/Listening.jpg'} + content = {'Topic': 'Unreal', 'Data': {'Key': 'log', 'Value': "唤醒成功！"}, + 'Username': self.username, + 'robot': f'http://{cfg.fay_url}:5000/robot/Listening.jpg'} wsa_server.get_instance().add_cmd(content) - #去除唤醒词后语句 - question = text#[len(wake_up_word):].lstrip() - self.on_speaking(question) + + # 在识别到【前置唤醒词】后，发送“去掉唤醒词后的问题” + if question: + self.on_speaking(question) + else: + intt = interact.Interact("auto_play", 2, {'user': self.username, 'text': "在呢，你说？"}) + self.__fay.on_interact(intt) + self.processing = False else: util.printInfo(1, self.username, "[!] 待唤醒！") if wsa_server.get_web_instance().is_connected(self.username): - wsa_server.get_web_instance().add_cmd({"panelMsg": "[!] 待唤醒！", "Username" : self.username , 'robot': f'http://{cfg.fay_url}:5000/robot/Normal.jpg'}) + wsa_server.get_web_instance().add_cmd({"panelMsg": "[!] 待唤醒！", "Username": self.username, + 'robot': f'http://{cfg.fay_url}:5000/robot/Normal.jpg'}) if wsa_server.get_instance().is_connected(self.username): - content = {'Topic': 'Unreal', 'Data': {'Key': 'log', 'Value': "[!] 待唤醒！"}, 'Username' : self.username, 'robot': f'http://{cfg.fay_url}:5000/robot/Normal.jpg'} + content = {'Topic': 'Unreal', 'Data': {'Key': 'log', 'Value': "[!] 待唤醒！"}, + 'Username': self.username, + 'robot': f'http://{cfg.fay_url}:5000/robot/Normal.jpg'} wsa_server.get_instance().add_cmd(content) + self.processing = False #非唤醒模式 else: @@ -220,12 +287,8 @@ class Recorder: continue #是否可以拾音,不可以就掉弃录音 can_listen = True - #没有开唤醒，但面板或数字人正在播音时不能拾音 - if cfg.config['source']['wake_word_enabled'] == False and self.__fay.speaking == True: - can_listen = False - - #普通唤醒模式已经激活，并且面板或数字人正在输出声音时不能拾音 - if cfg.config['source']['wake_word_enabled'] == True and cfg.config['source']['wake_word_type'] == 'common' and self.wakeup_matched == True and self.__fay.speaking == True: + if self.__fay.speaking == True: + # 只要数字人/面板在播放TTS，就禁拾音，避免把自己的声音识别成用户输入 can_listen = False if can_listen == False:#掉弃录音 @@ -234,7 +297,7 @@ class Recorder: #计算音量是否满足激活拾音 level = audioop.rms(data, 2) - if len(self.__history_data) >= 10:#保存激活前的音频，以免信息掉失 + if len(self.__history_data) >= 20:#保存激活前的音频，以免信息掉失 self.__history_data.pop(0) if len(self.__history_level) >= 500: self.__history_level.pop(0) @@ -242,12 +305,19 @@ class Recorder: self.__history_level.append(level) percentage = level / self.__MAX_LEVEL history_percentage = self.__get_history_percentage(30) + + # ===== 改进：阈值平滑变化，避免断句导致唤醒词被截断 ===== + up_alpha = 0.01 # 环境变吵：慢慢升 + down_alpha = 0.05 # 环境变安静：也不要瞬间掉 + if history_percentage > self.__dynamic_threshold: - self.__dynamic_threshold += (history_percentage - self.__dynamic_threshold) * 0.0025 - elif history_percentage < self.__dynamic_threshold: - self.__dynamic_threshold += (history_percentage - self.__dynamic_threshold) * 1 - - + self.__dynamic_threshold += (history_percentage - self.__dynamic_threshold) * up_alpha + else: + self.__dynamic_threshold += (history_percentage - self.__dynamic_threshold) * down_alpha + + # 给阈值一个下限，防止过度灵敏 + self.__dynamic_threshold = max(self.__dynamic_threshold, 0.02) + #激活拾音 if percentage > self.__dynamic_threshold: last_speaking_time = time.time()