Search Results for author:
Found 6 papers, 3 papers with code
Towards Massive Multilingual Holistic Bias
In the current landscape of automatic language generation, there is a need to understand, evaluate, and mitigate demographic biases as existing models are becoming increasingly multilingual.
MuTox: Universal MUltilingual Audio-based TOXicity Dataset and Zero-shot Detector
Research in toxicity detection in natural language processing for the speech modality (audio-based) is quite limited, particularly for languages other than English.
Audiobox: Unified Audio Generation with Natural Language Prompts
Research communities have made great progress over the past year advancing the performance of large scale audio generative models for a single modality (speech, sound, or music) through adopting more powerful generative models and scaling data.
Ranked #1 on
Audio Generation
on AudioCaps
Seamless: Multilingual Expressive and Streaming Speech Translation
In this work, we introduce a family of models that enable end-to-end expressive and multilingual translations in a streaming fashion.
automatic-speech-translation
Multimodal Machine Translation
+1
SeamlessM4T: Massively Multilingual & Multimodal Machine Translation
What does it take to create the Babel Fish, a tool that can help individuals translate speech between any two languages?
Ranked #1 on
Speech-to-Speech Translation
on CVSS
(using extra training data)
Automatic Speech Recognition
Speech-to-Speech Translation
+4
Multilingual Holistic Bias: Extending Descriptors and Patterns to Unveil Demographic Biases in Languages at Scale
Our initial findings show that translation quality for EN-to-XX translations is an average of 8 spBLEU better when evaluating with the masculine human reference compared to feminine.
