#speech processing

Athena is an open-source engine for end-to-end speech processing, suitable for both industrial and research applications. Built on Tensorflow, it includes models for tasks such as ASR, TTS, VAD, and KWS. Athena supports hybrid attention/CTC models, multi-GPU training with Horovod, and WFST-based decoding. Recent enhancements allow Tensorflow C++ deployment and introduce models like AV-Transformer and Conformer-CTC. The platform aims to make advanced speech processing accessible to all, backed by thorough documentation and community resources.

Codec-SUPERB offers a rigorous platform for evaluating audio codec models in diverse speech tasks. It enhances speech information quality and promotes community collaboration with an easy-to-use codec interface and a transparent multiperspective leaderboard. Its standardized testing environment and unified datasets ensure fair comparisons, making it essential for advancing research in sound codec models.

VoiceFlow uses rectified flow matching to improve the efficiency and quality of text-to-speech synthesis. This ICASSP 2024 paper offers a detailed implementation guide covering environment setup, data preparation, training, and inference. The project advances flow matching and employs rectified flows to enhance performance and accuracy. The repository provides utility scripts and model configurations, allowing for customization across various datasets. It also presents experimental functions such as voice conversion and likelihood estimation, broadening the capabilities of flow matching in speech synthesis. Aimed at developers looking for efficient TTS solutions.

Lhotse, a Python library, enhances speech and audio data preparation by offering flexible and accessible solutions. It smoothly integrates with PyTorch and supports both novice and seasoned users with its command-line interface and standardized data preparation methods. Lhotse's features include dynamic audio cuts for real-time operations like mixing and truncation, optimizing storage and bandwidth usage. It allows for data augmentation and feature extraction in both pre-computed and real-time modes, supports feature-space cut mixing, and works with Kaldi and ESPnet frameworks, making it a valuable tool for researchers and developers in audio processing.

SpeechBrain, an open-source PyTorch toolkit, simplifies Conversational AI development with over 200 training recipes for speech and text processing tasks. It includes capabilities like speech recognition, speaker recognition, and speech enhancement, suitable for rapid prototyping and educational use. The toolkit integrates easily with HuggingFace pretrained models and offers extensive documentation, facilitating research and development in complex AI systems. Discover its features and models tailored for diverse AI applications, balancing ease of use with advanced technical capabilities.

AgentLego is an open-source library providing versatile tool APIs that expand and enhance large language model (LLM) agents. It includes a variety of multimodal tools such as visual perception, image generation, and speech processing. These tools are easily integrable with custom interfaces and support remote access for computationally intensive applications. Integration is seamless with popular frameworks like LangChain, Transformers Agents, and Lagent. Explore these tools to boost the capabilities of your LLM-based projects.