62 citations · 655 across the 97 of their papers we have counts for
14 papers · 1 filter
Open Source MagicData-RAMC: A Rich Annotated Mandarin Conversational(RAMC) Speech Dataset
Zehui Yang, Yifan Chen, Lei Luo +9
This paper introduces a high-quality rich annotated Mandarin conversational (RAMC) speech dataset called MagicData-RAMC. The MagicData-RAMC corpus contains 180 hours of conversatio…
Wake Word Detection with Streaming Transformers
Yiming Wang, Hang Lv, Daniel Povey +2
Modern wake word detection systems usually rely on neural networks for acoustic modeling. Transformers has recently shown superior performance over LSTM and convolutional networks…
Espresso: A Fast End-to-end Neural Speech Recognition Toolkit
Yiming Wang, Tongfei Chen, Hainan Xu +7
We present Espresso, an open-source, modular, extensible end-to-end neural automatic speech recognition (ASR) toolkit based on the deep learning library PyTorch and the popular neu…
A New GAN-based End-to-End TTS Training Algorithm
Haohan Guo, Frank K. Soong, Lei He +1
End-to-end, autoregressive model-based TTS has shown significant performance improvements over the conventional one. However, the autoregressive module training is affected by the…
Exploiting Syntactic Features in a Parsed Tree to Improve End-to-End TTS
Haohan Guo, Frank K. Soong, Lei He +1
The end-to-end TTS, which can predict speech directly from a given sequence of graphemes or phonemes, has shown improved performance over the conventional TTS. However, its predict…
Building a mixed-lingual neural TTS system with only monolingual data
Liumeng Xue, Wei Song, Guanghui Xu +2
When deploying a Chinese neural text-to-speech (TTS) synthesis system, one of the challenges is to synthesize Chinese utterances with English phrases or words embedded. This paper…
Exploring RNN-Transducer for Chinese Speech Recognition
Senmao Wang, Pan Zhou, Wei Chen +2
End-to-end approaches have drawn much attention recently for significantly simplifying the construction of an automatic speech recognition (ASR) system. RNN transducer (RNN-T) is o…
Learning Acoustic Word Embeddings with Temporal Context for Query-by-Example Speech Search
Yougen Yuan, Cheung-Chi Leung, Lei Xie +3
We propose to learn acoustic word embeddings with temporal context for query-by-example (QbE) speech search. The temporal context includes the leading and trailing word sequences o…
Training Augmentation with Adversarial Examples for Robust Speech Recognition
Sining Sun, Ching-Feng Yeh, Mari Ostendorf +2
This paper explores the use of adversarial examples in training speech recognition systems to increase robustness of deep neural network acoustic models. During training, the fast…
Study of Semi-supervised Approaches to Improving English-Mandarin Code-Switching Speech Recognition
Pengcheng Guo, Haihua Xu, Lei Xie +1
In this paper, we present our overall efforts to improve the performance of a code-switching speech recognition system using semi-supervised training methods from lexicon learning…
Domain Adversarial Training for Accented Speech Recognition
Sining Sun, Ching-Feng Yeh, Mei-Yuh Hwang +2
In this paper, we propose a domain adversarial training (DAT) algorithm to alleviate the accented speech recognition problem. In order to reduce the mismatch between labeled source…
Attention-Based End-to-End Speech Recognition on Voice Search
Changhao Shan, Junbo Zhang, Yujun Wang +1
Recently, there has been a growing interest in end-to-end speech recognition that directly transcribes speech to text without any predefined alignments. In this paper, we explore t…
Empirical Evaluation of Parallel Training Algorithms on Acoustic Modeling
Wenpeng Li, BinBin Zhang, Lei Xie +1
Deep learning models (DLMs) are state-of-the-art techniques in speech recognition. However, training good DLMs can be time consuming especially for production-size models and corpo…
Automatic Prosody Prediction for Chinese Speech Synthesis using BLSTM-RNN and Embedding Features
Chuang Ding, Lei Xie, Jie Yan +2
Prosody affects the naturalness and intelligibility of speech. However, automatic prosody prediction from text for Chinese speech synthesis is still a great challenge and the tradi…