6 citations · 8 across the 14 of their papers we have counts for
14 papers
STEB: A Speech-to-Speech Translation Expressiveness Benchmark for Evaluating Beyond Translation Fidelity
Sitong Cheng, Weizhen Bian, Songjun Cao +9
Speech-to-speech translation (S2ST) should preserve not only lexical meaning, but also expressive attributes: emotion, scenario style (e.g., news reporting vs. dramatic dialogue),…
LUCY: Linguistic Understanding and Control Yielding Early Stage of Her
Heting Gao, Hang Shao, Xiong Wang +12
The film Her features Samantha, a sophisticated AI audio agent who is capable of understanding both linguistic and paralinguistic information in human speech and delivering real-ti…
FreeCodec: A disentangled neural speech codec with fewer tokens
Youqiang Zheng, Weiping Tu, Yueteng Kang +5
Neural speech codecs have gained great attention for their outstanding reconstruction with discrete token representations. It is a crucial component in generative tasks such as spe…
A Transcription Prompt-based Efficient Audio Large Language Model for Robust Speech Recognition
Yangze Li, Xiong Wang, Songjun Cao +3
Audio-LLM introduces audio modality into a large language model (LLM) to enable a powerful LLM to recognize, understand, and generate audio. However, during speech recognition in n…
FocusLLM: Precise Understanding of Long Context by Dynamic Condensing
Zhenyu Li, Yike Zhang, Tengyu Pan +6
Empowering LLMs with the ability to precisely understand long contexts is crucial for many downstream applications. However, handling long contexts with conventional transformer ar…
Two Stage Contextual Word Filtering for Context bias in Unified Streaming and Non-streaming Transducer
Zhanheng Yang, Sining Sun, Xiong Wang +3
It is difficult for an E2E ASR system to recognize words such as entities appearing infrequently in the training data. A widely used method to mitigate this issue is feeding contex…
Leveraging Acoustic Contextual Representation by Audio-textual Cross-modal Learning for Conversational ASR
Kun Wei, Yike Zhang, Sining Sun +2
Leveraging context information is an intuitive idea to improve performance on conversational automatic speech recognition(ASR). Previous works usually adopt recognized hypotheses o…
Censer: Curriculum Semi-supervised Learning for Speech Recognition Based on Self-supervised Pre-training
Bowen Zhang, Songjun Cao, Xiaoming Zhang +3
Recent studies have shown that the benefits provided by self-supervised pre-training and self-training (pseudo-labeling) are complementary. Semi-supervised fine-tuning strategies u…
A practical framework for multi-domain speech recognition and an instance sampling method to neural language modeling
Yike Zhang, Xiaobing Feng, Yi Liu +2
Automatic speech recognition (ASR) systems used on smart phones or vehicles are usually required to process speech queries from very different domains. In such situations, a vanill…
Improving CTC-based speech recognition via knowledge transferring from pre-trained language models
Keqi Deng, Songjun Cao, Yike Zhang +4
Recently, end-to-end automatic speech recognition models based on connectionist temporal classification (CTC) have achieved impressive results, especially when fine-tuned from wav2…
Conversational Speech Recognition By Learning Conversation-level Characteristics
Kun Wei, Yike Zhang, Sining Sun +2
Conversational automatic speech recognition (ASR) is a task to recognize conversational speech including multiple speakers. Unlike sentence-level ASR, conversational ASR can natura…
Improving Hybrid CTC/Attention End-to-end Speech Recognition with Pretrained Acoustic and Language Model
Keqi Deng, Songjun Cao, Yike Zhang +1
Recently, self-supervised pretraining has achieved impressive results in end-to-end (E2E) automatic speech recognition (ASR). However, the dominant sequence-to-sequence (S2S) E2E m…
Improving Streaming Transformer Based ASR Under a Framework of Self-supervised Learning
Songjun Cao, Yueteng Kang, Yanzhe Fu +4
Recently self-supervised learning has emerged as an effective approach to improve the performance of automatic speech recognition (ASR). Under such a framework, the neural network…
Improving Speech Recognition Accuracy of Local POI Using Geographical Models
Songjun Cao, Yike Zhang, Xiaobing Feng +1
Nowadays voice search for points of interest (POI) is becoming increasingly popular. However, speech recognition for local POI has remained to be a challenge due to multi-dialect a…