Expanding the language coverage of speech technology has the potential to improve
access to information for many more people. However, current speech technology is …

We introduce the Universal Speech Model (USM), a single large model that performs
automatic speech recognition (ASR) across 100+ languages. This is achieved by pre …

Speech processing Universal PERformance Benchmark (SUPERB) is a leaderboard to
benchmark the performance of Self-Supervised Learning (SSL) models on various speech …

With the emergence of deep learning, the performance of automatic speech recognition
(ASR) systems has remarkably improved. Especially for resource-rich languages such as …

Multilingual Automatic Speech Recognition (ASR) models have extended the usability of
speech technologies to a wide variety of languages. With how many languages these …

Research on speech-to-speech translation (S2ST) has progressed rapidly in recent years.
Many end-to-end systems have been proposed and show advantages over conventional …

The 2023 Multilingual Speech Universal Performance Benchmark (ML-SUPERB) Challenge
expands upon the acclaimed SUPERB framework, emphasizing self-supervised models in …

In this work, we seek to build effective code-switched (CS) automatic speech recognition
systems (ASR) under the zero-shot set-ting where no transcribed CS speech data is …

While neural text-to-speech (TTS) has achieved human-like natural synthetic speech,
multilingual TTS systems are limited to resource-rich languages due to the need for paired …

In the field of spoken language understanding, systems like Whisper and Multilingual
Massive Speech (MMS) have shown state-of-the-art performances. This study is dedicated …