In a recent study published in the newspaper SpeechVerse, a team at Amazon AWS AI Labs introduces SpeechVerse, a new audio-language framework named SpeechVerse. The framework leverages supervised instruction tuning to achieve robust performance on a variety of speech tasks, including ASR, spoken language comprehension, and paralinguistic speaking tasks.
The team’s main contributions include scalable multimodal instruction tuning, versatile instruction following capability, and strategies to improve generalization. The researchers developed a multimodal model architecture comprising a pre-trained audio encoder, a 1-D convolution module, and a pre-trained LLM to perform various tasks.
Three variants of multimodal models were developed using the SpeechVerse framework: Task-FT, Multitask-WLM, and Multitask-BRQ. In empirical studies, the researchers compared their models to a waterfall baseline using LLM on ASR assumptions. SpeechVerse outperformed conventional baselines on 9 of 11 tasks and maintained strong performance on out-of-domain data sets, unseen prompts, and even unseen tasks.
Future plans for SpeechVerse include improving its capabilities to follow more complex instructions and generalize to new domains. The framework represents a versatile tool that can adapt to new tasks without the need for retraining. Subscribe to the newsletter Global AI synchronized weekly for updates on AI research and breakthroughs.
In conclusion, SpeechVerse is an innovative audio-language framework developed by a research team at Amazon AWS AI Labs. The framework leverages supervised instruction tuning to achieve robust performance on a variety of speech tasks. The researchers have made significant contributions in scalable multimodal instruction tuning, versatile instruction following capability, and strategies to improve generalization. The proposed multimodal model architecture consists of a pre-trained audio encoder, a 1-D convolution module, and a pre-trained LLM. Three variants of multimodal models were developed using the SpeechVerse framework, with empirical studies showing that SpeechVerse outperformed conventional baselines on most tasks. Future plans for SpeechVerse include improving its capabilities and generalization ability. Subscribe to the newsletter Global AI synchronized weekly for updates on AI research.
Article Source
https://syncedreview.com/2024/05/21/generalizable-audio-ai-discover-the-power-of-speechverse-by-amazon-aws-ai-labs/
