AsrTools is an AI-powered speech-to-text tool that utilizes major ASR service interfaces to provide efficient speech recognition without requiring GPU or complex configurations. This tool supports batch processing and multithreading, allowing rapid conversion of audio files into SRT or TXT subtitle files. The user interface of AsrTools, built with PyQt5 and qfluentwidgets, offers an attractive and easy-to-navigate experience. Key advantages include stable integration with major service interfaces, convenience without complex setups, and flexibility in output formats. AsrTools is ideal for users who need to quickly convert speech content into text, especially in fields like video production, audio editing, and subtitle generation. Currently, AsrTools offers a free usage model for major ASR services, significantly reducing costs and enhancing workflow efficiency for individuals and small teams.

seed-vc is a voice conversion model based on the SEED-TTS architecture, capable of zero-shot voice conversion, meaning it can convert voices without requiring specific voice samples from individuals. This technology excels in audio quality and tonal similarity, holding substantial research and application value.

OptiSpeech is an efficient, lightweight, and fast text-to-speech model specifically designed for device-side text-to-speech conversion. Leveraging advanced deep learning techniques, it converts text into naturally sounding speech, making it suitable for applications that require speech synthesis on mobile devices or embedded systems. The development of OptiSpeech was significantly accelerated by GPU resources provided by Pneuma Solutions.

speech-to-speech is an open-source modular GPT4-o project that achieves speech-to-speech conversion through sequential components such as voice activity detection, speech-to-text, language modeling, and text-to-speech synthesis. It leverages the Transformers library and models available on the Hugging Face hub, providing a high degree of modularity and flexibility.

Pandrator is a tool based on open-source software that converts text, PDF, EPUB, and SRT files into voice audio in multiple languages. It includes features for voice cloning, LLM-based text preprocessing, and directly saving generated audio subtitles into video files, blending them with original audio tracks. It is designed for ease of use and installation, featuring a one-click installer and a graphical user interface.

FunAudioLLM is a framework aimed at enhancing natural voice interaction between humans and Large Language Models (LLMs). It comprises two innovative models: SenseVoice, responsible for high-precision multi-lingual speech recognition, emotion recognition, and audio event detection; and CosyVoice, responsible for natural voice generation, supporting multi-lingual, timbre, and emotion control. SenseVoice supports over 50 languages with extremely low latency; CosyVoice excels in multi-lingual voice generation, zero-shot context generation, cross-lingual voice cloning, and instruction following capabilities. Relevant models are open-sourced on Modelscope and Huggingface, and corresponding training, inference, and fine-tuning codes are released on GitHub.

ChatTTS-Forge is a project built around the ChatTTS text-to-speech generation model. It provides a comprehensive API service and a Gradio-based WebUI, enabling the generation of long texts exceeding 1000 words while maintaining consistency. The platform boasts built-in style management with 32 distinct styles.

ChatTTS-ui is a web interface and API interface for the ChatTTS project. It allows users to perform text-to-speech operations through a webpage and remotely call the service through an API interface. It supports multiple voice options, and users can customize the text-to-speech parameters, such as adding laughter or pauses. This project provides an easy-to-use interface for text-to-speech technology, lowering the technical barrier and making text-to-speech more convenient.

ChatTTS is an open-source text-to-speech (TTS) model that allows users to convert text into speech. This model is primarily aimed at academic research and educational purposes and is not suitable for commercial or legal applications. It utilizes deep learning techniques to generate natural and fluent speech output, making it suitable for individuals involved in speech synthesis research and development.

AsrTools is an AI-powered speech-to-text tool that utilizes major ASR service interfaces to provide efficient speech recognition without requiring GPU or complex configurations. This tool supports batch processing and multithreading, allowing rapid conversion of audio files into SRT or TXT subtitle files. The user interface of AsrTools, built with PyQt5 and qfluentwidgets, offers an attractive and easy-to-navigate experience. Key advantages include stable integration with major service interfaces, convenience without complex setups, and flexibility in output formats. AsrTools is ideal for users who need to quickly convert speech content into text, especially in fields like video production, audio editing, and subtitle generation. Currently, AsrTools offers a free usage model for major ASR services, significantly reducing costs and enhancing workflow efficiency for individuals and small teams.

seed-vc is a voice conversion model based on the SEED-TTS architecture, capable of zero-shot voice conversion, meaning it can convert voices without requiring specific voice samples from individuals. This technology excels in audio quality and tonal similarity, holding substantial research and application value.

OptiSpeech is an efficient, lightweight, and fast text-to-speech model specifically designed for device-side text-to-speech conversion. Leveraging advanced deep learning techniques, it converts text into naturally sounding speech, making it suitable for applications that require speech synthesis on mobile devices or embedded systems. The development of OptiSpeech was significantly accelerated by GPU resources provided by Pneuma Solutions.

speech-to-speech is an open-source modular GPT4-o project that achieves speech-to-speech conversion through sequential components such as voice activity detection, speech-to-text, language modeling, and text-to-speech synthesis. It leverages the Transformers library and models available on the Hugging Face hub, providing a high degree of modularity and flexibility.

Pandrator is a tool based on open-source software that converts text, PDF, EPUB, and SRT files into voice audio in multiple languages. It includes features for voice cloning, LLM-based text preprocessing, and directly saving generated audio subtitles into video files, blending them with original audio tracks. It is designed for ease of use and installation, featuring a one-click installer and a graphical user interface.

FunAudioLLM is a framework aimed at enhancing natural voice interaction between humans and Large Language Models (LLMs). It comprises two innovative models: SenseVoice, responsible for high-precision multi-lingual speech recognition, emotion recognition, and audio event detection; and CosyVoice, responsible for natural voice generation, supporting multi-lingual, timbre, and emotion control. SenseVoice supports over 50 languages with extremely low latency; CosyVoice excels in multi-lingual voice generation, zero-shot context generation, cross-lingual voice cloning, and instruction following capabilities. Relevant models are open-sourced on Modelscope and Huggingface, and corresponding training, inference, and fine-tuning codes are released on GitHub.

ChatTTS-Forge is a project built around the ChatTTS text-to-speech generation model. It provides a comprehensive API service and a Gradio-based WebUI, enabling the generation of long texts exceeding 1000 words while maintaining consistency. The platform boasts built-in style management with 32 distinct styles.

ChatTTS-ui is a web interface and API interface for the ChatTTS project. It allows users to perform text-to-speech operations through a webpage and remotely call the service through an API interface. It supports multiple voice options, and users can customize the text-to-speech parameters, such as adding laughter or pauses. This project provides an easy-to-use interface for text-to-speech technology, lowering the technical barrier and making text-to-speech more convenient.