Self-supervised speech representation learning: A review
Although supervised deep learning has revolutionized speech and audio processing, it has
necessitated the building of specialist models for individual tasks and application scenarios …
necessitated the building of specialist models for individual tasks and application scenarios …
Sparks of large audio models: A survey and outlook
This survey paper provides a comprehensive overview of the recent advancements and
challenges in applying large language models to the field of audio signal processing. Audio …
challenges in applying large language models to the field of audio signal processing. Audio …
The llama 3 herd of models
Modern artificial intelligence (AI) systems are powered by foundation models. This paper
presents a new set of foundation models, called Llama 3. It is a herd of language models …
presents a new set of foundation models, called Llama 3. It is a herd of language models …
Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context
G Team, P Georgiev, VI Lei, R Burnell, L Bai… - arxiv preprint arxiv …, 2024 - arxiv.org
In this report, we introduce the Gemini 1.5 family of models, representing the next generation
of highly compute-efficient multimodal models capable of recalling and reasoning over fine …
of highly compute-efficient multimodal models capable of recalling and reasoning over fine …
Scaling speech technology to 1,000+ languages
Expanding the language coverage of speech technology has the potential to improve
access to information for many more people. However, current speech technology is …
access to information for many more people. However, current speech technology is …
Robust speech recognition via large-scale weak supervision
We study the capabilities of speech processing systems trained simply to predict large
amounts of transcripts of audio on the internet. When scaled to 680,000 hours of multilingual …
amounts of transcripts of audio on the internet. When scaled to 680,000 hours of multilingual …
Google usm: Scaling automatic speech recognition beyond 100 languages
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 …
automatic speech recognition (ASR) across 100+ languages. This is achieved by pre …
Wavlm: Large-scale self-supervised pre-training for full stack speech processing
Self-supervised learning (SSL) achieves great success in speech recognition, while limited
exploration has been attempted for other speech processing tasks. As speech signal …
exploration has been attempted for other speech processing tasks. As speech signal …
XLS-R: Self-supervised cross-lingual speech representation learning at scale
This paper presents XLS-R, a large-scale model for cross-lingual speech representation
learning based on wav2vec 2.0. We train models with up to 2B parameters on nearly half a …
learning based on wav2vec 2.0. We train models with up to 2B parameters on nearly half a …
Dawn of the transformer era in speech emotion recognition: closing the valence gap
Recent advances in transformer-based architectures have shown promise in several
machine learning tasks. In the audio domain, such architectures have been successfully …
machine learning tasks. In the audio domain, such architectures have been successfully …