VoiceInputFix (Fun-ASR / SenseVoice Edition)
Description
VoiceInputFix is a replacement for the default speech recognition system in YAPYAP. It swaps the original Vosk engine with Fun-ASR (SenseVoice) to provide:
- Higher Accuracy: More reliable command recognition.
- Multi-language Support: Automatically recognizes Chinese (Mandarin/Cantonese)/English/Japanese/Korean. Now supports manual configuration to prioritize a specific language for better stability.
- Lower Latency: Faster response times for voice commands.
Dependencies
This mod requires the SherpaOnnxRuntime package to function. Please ensure it is installed. It provides the necessary core libraries:
onnxruntime.dllsherpa-onnx-c-api.dllsherpa-onnx.dll
Download Models
You must download the following files for the mod to work:
- model.onnx (1.03GB): Download
- tokens.txt (940KB): Download (If the link opens in your browser, press Ctrl+S to save, or right-click the link and select "Save Link As...")
Installation
- Critical:
VoiceInputFix.dll and the models folder MUST be in the same directory.
- You can place them directly into
BepInEx/plugins/, or within a subfolder like BepInEx/plugins/VoiceInputFix/.
- Place the downloaded
model.onnx and tokens.txt inside the models folder.
- Example path:
BepInEx/plugins/VoiceInputFix/models/model.onnx
Performance Characteristics
- Initial Loading: The game will experience a significant screen freeze when the engine initializes for the very first time. This is normal behavior while the 1GB model is being loaded into memory.
- Menu Reloading: When returning to the main menu and re-entering the game, there is a loading delay for the model, but it will not freeze the screen again.
- Gameplay: Once you enter a level, the recognition is smooth and available immediately with no impact on game performance.
Advanced Configuration
Config file path: BepInEx/config/Mhz.voiceinputfix.cfg
- SpeechThreshold (Default: 0.015)
This is the "Noise Gate". It determines the volume required to trigger recognition.
- If the mod captures background noise or text stays on screen too long: Increase this value (e.g., 0.025).
- If you have to shout to be heard: Decrease this value (e.g., 0.010).
- Language (Default: auto)
Specifies the language for recognition. While "auto" works for multiple languages, selecting a specific one improves recognition accuracy and reduces errors.
- auto: Detect all supported languages automatically: Chinese (Mandarin/Cantonese)/English/Japanese/Korean.
- zh, en, ja, ko, yue: Enhance the recognition weight for the selected language. Note: This prioritizes matching the chosen language but does not strictly lock it; if an utterance sounds extremely similar to another language, it may still be recognized as such.
- EnableDebugLog (Default: false)
VoiceInputFix (Fun-ASR / SenseVoice 版)
模组简介
VoiceInputFix 是一款改进《YAPYAP》语音识别体验的模组。它将游戏原有的 Vosk 引擎替换为 Fun-ASR (SenseVoice)，主要改进包括：
- 识别更精准：有效减少指令识别错误的情况。
- 多语言支持：默认自动识别中（普通话/粤语）/英/日/韩语。支持手动指定语言以显著提高特定语言的识别稳定性，减少环境干扰。
- 更低延迟：语音指令的响应速度比原版更快。
必需依赖项
本模组需要安装 SherpaOnnxRuntime 运行库模组才能正常工作。它包含以下核心组件：
onnxruntime.dllsherpa-onnx-c-api.dllsherpa-onnx.dll
模型下载
必须下载以下两个文件，模组才能运行：
- model.onnx (1.03GB): 点击下载
- tokens.txt (940KB): 点击下载 (若点击后直接打开，请在网页中按 Ctrl+S 保存，或右键点击下载链接选择“链接另存为”)
安装步骤
- 核心原则：
VoiceInputFix.dll 与 models 文件夹必须位于同一目录下。
- 你可以将它们直接放入
BepInEx/plugins 目录，也可以放入 plugins 下的任意子文件夹内（注意：文件夹路径请勿包含中文字符。例如 BepInEx/plugins/VoiceInputFix/）。
- 将下载好的
model.onnx 和 tokens.txt 放入 models 文件夹内。
- 示例路径：
BepInEx/plugins/VoiceInputFix/models/model.onnx
运行特性
- 首次加载：第一次启动语音引擎时，会出现一次较长时间的屏幕卡顿（画面静止）。这是正在将大型模型载入内存，属于正常现象，请耐心等待加载完成。
- 重连加载：返回主菜单并重新进入游戏时，会有短暂的模型重载等待时间，但不会再次导致画面卡死。
- 关卡表现：正式进入关卡后，功能可立即使用，运行流畅且不占用额外的游戏帧率。
进阶配置
配置文件路径：BepInEx/config/Mhz.voiceinputfix.cfg
- SpeechThreshold (默认值: 0.015)
这是语音检测的“分贝门槛”。
- 如果环境吵闹导致文字不消失：请调高此值（例如 0.025 或 0.03）。
- 如果说话必须很大声才能识别：请调低此值（例如 0.010）。
- Language (默认值: auto)
指定识别语言。虽然 "auto" 可以自动处理多语言，但指定特定语言可以显著提高识别率并减少识别错误。
- auto: 自动识别所有支持的语言：中（普通话/粤语）/ 英 / 日 / 韩语。
- zh, en, ja, ko, yue: 增强所选语言的识别权重。注意：这仅代表系统会【优先】匹配该语言，并不代表完全锁死；如果发音特征与其它语言极度相似，系统仍可能识别为其它语言。
- EnableDebugLog (默认值: false)
