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Salm: Speech-augmented language model with in-context learning for speech recognition and translation
We present a novel Speech Augmented Language Model (SALM) with multitask and in-
context learning capabilities. SALM comprises a frozen text LLM, a audio encoder, a …
context learning capabilities. SALM comprises a frozen text LLM, a audio encoder, a …
Contextualized end-to-end automatic speech recognition with intermediate biasing loss
Contextualized end-to-end automatic speech recognition has been an active research area,
with recent efforts focusing on the implicit learning of contextual phrases based on the final …
with recent efforts focusing on the implicit learning of contextual phrases based on the final …
Phoneme-aware encoding for prefix-tree-based contextual ASR
In speech recognition applications, it is important to recognize context-specific rare words,
such as proper nouns. Tree-constrained Pointer Generator (TCPGen) has shown promise …
such as proper nouns. Tree-constrained Pointer Generator (TCPGen) has shown promise …
Adapting OpenAI's Whisper for speech recognition on code-switch mandarin-english seame and asru2019 datasets
This paper reports on SOTA results achieved using openAI's Whisper model with adaptation
on different adaptation corpus sizes for two established code-switch Mandarin/English …
on different adaptation corpus sizes for two established code-switch Mandarin/English …
Keyword-guided adaptation of automatic speech recognition
Automatic Speech Recognition (ASR) technology has made significant progress in recent
years, providing accurate transcription across various domains. However, some challenges …
years, providing accurate transcription across various domains. However, some challenges …
Improving Whisper's Recognition Performance for Under-Represented Language Kazakh Leveraging Unpaired Speech and Text
Whisper and other large-scale automatic speech recognition models have made significant
progress in performance. However, their performance on many low-resource languages …
progress in performance. However, their performance on many low-resource languages …
Mai Ho'om\= auna i ka'Ai: Language Models Improve Automatic Speech Recognition in Hawaiian
In this paper we address the challenge of improving Automatic Speech Recognition (ASR)
for a low-resource language, Hawaiian, by incorporating large amounts of independent text …
for a low-resource language, Hawaiian, by incorporating large amounts of independent text …
Speech-enriched memory for inference-time adaptation of asr models to word dictionaries
Despite the impressive performance of ASR models on mainstream benchmarks, their
performance on rare words is unsatisfactory. In enterprise settings, often a focused list of …
performance on rare words is unsatisfactory. In enterprise settings, often a focused list of …
[PDF][PDF] Contextual Biasing Speech Recognition in Speech-enhanced Large Language Model
Recently, the rapid advancements in audio-and speechenhanced large language models
(SpeechLLMs), such as Qwen-Audio and SALMONN, have significantly propelled automatic …
(SpeechLLMs), such as Qwen-Audio and SALMONN, have significantly propelled automatic …
Enhancing quantised end-to-end asr models via personalisation
Recent end-to-end automatic speech recognition (ASR) models have become increasingly
larger, making them particularly challenging to be deployed on resource-constrained …
larger, making them particularly challenging to be deployed on resource-constrained …