Search Results for author: Yichong Leng

Found 11 papers, 1 papers with code

BinauralGrad: A Two-Stage Conditional Diffusion Probabilistic Model for Binaural Audio Synthesis

no code implementations30 May 2022 Yichong Leng, Zehua Chen, Junliang Guo, Haohe Liu, Jiawei Chen, Xu Tan, Danilo Mandic, Lei He, Xiang-Yang Li, Tao Qin, Sheng Zhao, Tie-Yan Liu

Specifically, in the first stage, the common information of the binaural audio is generated with a single-channel diffusion model conditioned on the mono audio, based on which the binaural audio is generated by a two-channel diffusion model in the second stage.

Transcormer: Transformer for Sentence Scoring with Sliding Language Modeling

no code implementations25 May 2022 Kaitao Song, Yichong Leng, Xu Tan, Yicheng Zou, Tao Qin, Dongsheng Li

Previous works on sentence scoring mainly adopted either causal language modeling (CLM) like GPT or masked language modeling (MLM) like BERT, which have some limitations: 1) CLM only utilizes unidirectional information for the probability estimation of a sentence without considering bidirectional context, which affects the scoring quality; 2) MLM can only estimate the probability of partial tokens at a time and thus requires multiple forward passes to estimate the probability of the whole sentence, which incurs large computation and time cost.

Causal Language Modeling Language Modelling +2

NaturalSpeech: End-to-End Text to Speech Synthesis with Human-Level Quality

no code implementations9 May 2022 Xu Tan, Jiawei Chen, Haohe Liu, Jian Cong, Chen Zhang, Yanqing Liu, Xi Wang, Yichong Leng, YuanHao Yi, Lei He, Frank Soong, Tao Qin, Sheng Zhao, Tie-Yan Liu

In this paper, we answer these questions by first defining the human-level quality based on the statistical significance of subjective measure and introducing appropriate guidelines to judge it, and then developing a TTS system called NaturalSpeech that achieves human-level quality on a benchmark dataset.

Speech Synthesis Text-To-Speech Synthesis

Speech-T: Transducer for Text to Speech and Beyond

no code implementations NeurIPS 2021 Jiawei Chen, Xu Tan, Yichong Leng, Jin Xu, Guihua Wen, Tao Qin, Tie-Yan Liu

Experiments on LJSpeech datasets demonstrate that Speech-T 1) is more robust than the attention based autoregressive TTS model due to its inherent monotonic alignments between text and speech; 2) naturally supports streaming TTS with good voice quality; and 3) enjoys the benefit of joint modeling TTS and ASR in a single network.

Automatic Speech Recognition speech-recognition

A study on the efficacy of model pre-training in developing neural text-to-speech system

no code implementations8 Oct 2021 Guangyan Zhang, Yichong Leng, Daxin Tan, Ying Qin, Kaitao Song, Xu Tan, Sheng Zhao, Tan Lee

However, in terms of ultimately achieved system performance for target speaker(s), the actual benefits of model pre-training are uncertain and unstable, depending very much on the quantity and text content of training data.

FastCorrect 2: Fast Error Correction on Multiple Candidates for Automatic Speech Recognition

no code implementations Findings (EMNLP) 2021 Yichong Leng, Xu Tan, Rui Wang, Linchen Zhu, Jin Xu, Wenjie Liu, Linquan Liu, Tao Qin, Xiang-Yang Li, Edward Lin, Tie-Yan Liu

Although multiple candidates are generated by an ASR system through beam search, current error correction approaches can only correct one sentence at a time, failing to leverage the voting effect from multiple candidates to better detect and correct error tokens.

Automatic Speech Recognition speech-recognition

Analyzing and Mitigating Interference in Neural Architecture Search

no code implementations29 Aug 2021 Jin Xu, Xu Tan, Kaitao Song, Renqian Luo, Yichong Leng, Tao Qin, Tie-Yan Liu, Jian Li

In this paper, we investigate the interference issue by sampling different child models and calculating the gradient similarity of shared operators, and observe: 1) the interference on a shared operator between two child models is positively correlated with the number of different operators; 2) the interference is smaller when the inputs and outputs of the shared operator are more similar.

Neural Architecture Search Reading Comprehension

FastCorrect: Fast Error Correction with Edit Alignment for Automatic Speech Recognition

1 code implementation NeurIPS 2021 Yichong Leng, Xu Tan, Linchen Zhu, Jin Xu, Renqian Luo, Linquan Liu, Tao Qin, Xiang-Yang Li, Ed Lin, Tie-Yan Liu

A straightforward solution to reduce latency, inspired by non-autoregressive (NAR) neural machine translation, is to use an NAR sequence generation model for ASR error correction, which, however, comes at the cost of significantly increased ASR error rate.

Automatic Speech Recognition Machine Translation +2

A Study of Multilingual Neural Machine Translation

no code implementations25 Dec 2019 Xu Tan, Yichong Leng, Jiale Chen, Yi Ren, Tao Qin, Tie-Yan Liu

Multilingual neural machine translation (NMT) has recently been investigated from different aspects (e. g., pivot translation, zero-shot translation, fine-tuning, or training from scratch) and in different settings (e. g., rich resource and low resource, one-to-many, and many-to-one translation).

Machine Translation Translation

Unsupervised Pivot Translation for Distant Languages

no code implementations ACL 2019 Yichong Leng, Xu Tan, Tao Qin, Xiang-Yang Li, Tie-Yan Liu

In this work, we introduce unsupervised pivot translation for distant languages, which translates a language to a distant language through multiple hops, and the unsupervised translation on each hop is relatively easier than the original direct translation.

Machine Translation Translation

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