New solutions on LLM acceleration, optimization, and application
Large Language Models (LLMs) have revolutionized a wide range of applications with their
strong human-like understanding and creativity. Due to the continuously growing model size …
strong human-like understanding and creativity. Due to the continuously growing model size …
Acoustic model fusion for end-to-end speech recognition
Recent advances in deep learning and automatic speech recognition (ASR) have enabled
the end-to-end (E2E) ASR system and boosted the accuracy to a new level. The E2E …
the end-to-end (E2E) ASR system and boosted the accuracy to a new level. The E2E …
Retrieval augmented correction of named entity speech recognition errors
E Pusateri, A Walia, A Kashi, B Bandyopadhyay… - arXiv preprint arXiv …, 2024 - arxiv.org
In recent years, end-to-end automatic speech recognition (ASR) systems have proven
themselves remarkably accurate and performant, but these systems still have a significant …
themselves remarkably accurate and performant, but these systems still have a significant …
Improving Neural Biasing for Contextual Speech Recognition by Early Context Injection and Text Perturbation
Existing research suggests that automatic speech recognition (ASR) models can benefit
from additional contexts (eg, contact lists, user specified vocabulary). Rare words and …
from additional contexts (eg, contact lists, user specified vocabulary). Rare words and …
Conformer-based speech recognition on extreme edge-computing devices
With increasingly more powerful compute capabilities and resources in today's devices,
traditionally compute-intensive automatic speech recognition (ASR) has been moving from …
traditionally compute-intensive automatic speech recognition (ASR) has been moving from …
Contextualization of ASR with LLM using phonetic retrieval-based augmentation
Large language models (LLMs) have shown superb capability of modeling multimodal
signals including audio and text, allowing the model to generate spoken or textual response …
signals including audio and text, allowing the model to generate spoken or textual response …
Enhancing CTC-based speech recognition with diverse modeling units
In recent years, the evolution of end-to-end (E2E) automatic speech recognition (ASR)
models has been remarkable, largely due to advances in deep learning architectures like …
models has been remarkable, largely due to advances in deep learning architectures like …
AugMixSpeech: A Data Augmentation Method and Consistency Regularization for Mandarin Automatic Speech Recognition
Automatic speech recognition (ASR) is a crucial technology in the field of artificial
intelligence, widely applied in modern society. The deep learning-based ASR method offers …
intelligence, widely applied in modern society. The deep learning-based ASR method offers …