Reverb is an open-source inference codebase for speech recognition and speaker segmentation models, utilizing the WeNet framework for ASR and the Pyannote framework for speaker segmentation. It offers detailed model descriptions and allows users to download models from Hugging Face. Reverb aims to provide developers and researchers with high-quality tools for various speech processing tasks.

SpeechGPT2 is an end-to-end speech dialogue language model developed by the School of Computer Science at Fudan University. It can perceive and express emotions while providing appropriate voice responses in various styles based on context and human instructions. The model uses ultra-low bitrate speech codec (750bps) to simulate semantic and acoustic information and is initialized via a Multi-Input Multi-Output Language Model (MIMO-LM). Currently, SpeechGPT2 is a turn-based dialogue system, with development underway for a full-duplex real-time version that has shown promising progress. Despite limitations in computational and data resources, SpeechGPT2 has room for improvement regarding noise robustness in speech understanding and stability in speech generation quality, with plans for future open-source technical reports, code, and model weights.

Qwen2-Audio is a large audio language model proposed by Alibaba Cloud, capable of processing various audio signals as input and performing audio analysis or direct text reply based on speech commands. The model supports two different audio interaction modes: voice chat and audio analysis. It has achieved outstanding performance in 13 standard benchmark tests, including automatic speech recognition, speech-to-text translation, and speech emotion recognition.

Sherpa-onnx is a speech recognition and speech synthesis project based on the next-generation Kaldi, utilizing onnxruntime for inference. It supports a wide range of speech-related functionalities, including automatic speech recognition (ASR), text-to-speech (TTS), speaker recognition, speaker verification, language identification, and keyword detection. It is compatible with various platforms and operating systems, including embedded systems, Android, iOS, Raspberry Pi, RISC-V, and servers.

This is an Android voice assistant app developed based on the ChatGPT API. It supports voice interaction, continuous dialogue, and image recognition. Users can simply wake up the app and make voice inquiries from any interface by pressing the phone's volume buttons without typing, providing an excellent interactive experience. It also supports advanced features such as custom question templates, web scraping, and Vision image recognition.

Reverb is an open-source inference codebase for speech recognition and speaker segmentation models, utilizing the WeNet framework for ASR and the Pyannote framework for speaker segmentation. It offers detailed model descriptions and allows users to download models from Hugging Face. Reverb aims to provide developers and researchers with high-quality tools for various speech processing tasks.

SpeechGPT2 is an end-to-end speech dialogue language model developed by the School of Computer Science at Fudan University. It can perceive and express emotions while providing appropriate voice responses in various styles based on context and human instructions. The model uses ultra-low bitrate speech codec (750bps) to simulate semantic and acoustic information and is initialized via a Multi-Input Multi-Output Language Model (MIMO-LM). Currently, SpeechGPT2 is a turn-based dialogue system, with development underway for a full-duplex real-time version that has shown promising progress. Despite limitations in computational and data resources, SpeechGPT2 has room for improvement regarding noise robustness in speech understanding and stability in speech generation quality, with plans for future open-source technical reports, code, and model weights.

Qwen2-Audio is a large audio language model proposed by Alibaba Cloud, capable of processing various audio signals as input and performing audio analysis or direct text reply based on speech commands. The model supports two different audio interaction modes: voice chat and audio analysis. It has achieved outstanding performance in 13 standard benchmark tests, including automatic speech recognition, speech-to-text translation, and speech emotion recognition.

Sherpa-onnx is a speech recognition and speech synthesis project based on the next-generation Kaldi, utilizing onnxruntime for inference. It supports a wide range of speech-related functionalities, including automatic speech recognition (ASR), text-to-speech (TTS), speaker recognition, speaker verification, language identification, and keyword detection. It is compatible with various platforms and operating systems, including embedded systems, Android, iOS, Raspberry Pi, RISC-V, and servers.

This is an Android voice assistant app developed based on the ChatGPT API. It supports voice interaction, continuous dialogue, and image recognition. Users can simply wake up the app and make voice inquiries from any interface by pressing the phone's volume buttons without typing, providing an excellent interactive experience. It also supports advanced features such as custom question templates, web scraping, and Vision image recognition.