VERSA: A Versatile Evaluation Toolkit for Speech, Audio, and Music

2024-12-23

arXiv.org

AI Summary

To address the lack of unified, standardized evaluation tools for speech, audio, and music signals, this paper introduces the first cross-task, cross-modal, and configurable lightweight evaluation toolkit. The toolkit integrates 65 metrics and 729 configurable variants, supporting multi-source reference evaluation—including waveforms, text transcriptions, and semantic descriptions—across five downstream tasks: audio coding, speech synthesis, speech enhancement, singing voice synthesis, and music generation. Leveraging a Pythonic API, modular metric encapsulation, dependency isolation, and multimodal fusion evaluation techniques, it enables out-of-the-box, end-to-end assessment of both perceptual quality and semantic consistency. Extensive validation on multiple benchmarks confirms its metric diversity and configuration flexibility. The toolkit is open-sourced and has been widely adopted by the research community.

Technology Category

• Machine Learning: Multimodal Learning
• Natural Language Processing: Speech
• Computer Vision: Multi-modal Vision

Application Category

• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics
• Web Mining and Content Analysis: Mining multimedia, multimodal, multilingual, cross-lingual Web data
• User Modeling, Personalization and Recommendation: Metrics for user behavior and evaluating success

Abstract

In this work, we introduce VERSA, a unified and standardized evaluation toolkit designed for various speech, audio, and music signals. The toolkit features a Pythonic interface with flexible configuration and dependency control, making it user-friendly and efficient. With full installation, VERSA offers 65 metrics with 729 metric variations based on different configurations. These metrics encompass evaluations utilizing diverse external resources, including matching and non-matching reference audio, text transcriptions, and text captions. As a lightweight yet comprehensive toolkit, VERSA is versatile to support the evaluation of a wide range of downstream scenarios. To demonstrate its capabilities, this work highlights example use cases for VERSA, including audio coding, speech synthesis, speech enhancement, singing synthesis, and music generation. The toolkit is available at https://github.com/wavlab-speech/versa.

Problem

• Unified toolkit for speech, audio, and music evaluation
• Offers 65 metrics with 729 configurable variations
• Supports diverse scenarios like synthesis and enhancement

Innovation

• Pythonic interface with flexible configuration
• 65 metrics with 729 variations
• Supports diverse evaluation scenarios