158 citations · 895 across the 103 of their papers we have counts for
22 papers · 1 filter
Explicit Intensity Control for Accented Text-to-speech
Rui Liu, Haolin Zuo, De Hu +2
Accented text-to-speech (TTS) synthesis seeks to generate speech with an accent (L2) as a variant of the standard version (L1). How to control the intensity of accent in the proces…
CoBERT: Self-Supervised Speech Representation Learning Through Code Representation Learning
Chutong Meng, Junyi Ao, Tom Ko +2
Speech is the surface form of a finite set of phonetic units, which can be represented by discrete codes. We propose the Code BERT (CoBERT) approach for self-supervised speech repr…
Accurate Emotion Strength Assessment for Seen and Unseen Speech Based on Data-Driven Deep Learning
Rui Liu, Berrak Sisman, Björn Schuller +2
Emotion classification of speech and assessment of the emotion strength are required in applications such as emotional text-to-speech and voice conversion. The emotion attribute ra…
Genre-conditioned Acoustic Models for Automatic Lyrics Transcription of Polyphonic Music
Xiaoxue Gao, Chitralekha Gupta, Haizhou Li
Lyrics transcription of polyphonic music is challenging not only because the singing vocals are corrupted by the background music, but also because the background music and the sin…
Pre-Training Transformer Decoder for End-to-End ASR Model with Unpaired Speech Data
Junyi Ao, Ziqiang Zhang, Long Zhou +7
This paper studies a novel pre-training technique with unpaired speech data, Speech2C, for encoder-decoder based automatic speech recognition (ASR). Within a multi-task learning fr…
MFA: TDNN with Multi-scale Frequency-channel Attention for Text-independent Speaker Verification with Short Utterances
Tianchi Liu, Rohan Kumar Das, Kong Aik Lee +1
The time delay neural network (TDNN) represents one of the state-of-the-art of neural solutions to text-independent speaker verification. However, they require a large number of fi…
Emotion Intensity and its Control for Emotional Voice Conversion
Kun Zhou, Berrak Sisman, Rajib Rana +2
Emotional voice conversion (EVC) seeks to convert the emotional state of an utterance while preserving the linguistic content and speaker identity. In EVC, emotions are usually tre…
Time-Frequency Attention for Monaural Speech Enhancement
Qiquan Zhang, Qi Song, Zhaoheng Ni +2
Most studies on speech enhancement generally don't consider the energy distribution of speech in time-frequency (T-F) representation, which is important for accurate prediction of…
StrengthNet: Deep Learning-based Emotion Strength Assessment for Emotional Speech Synthesis
Rui Liu, Berrak Sisman, Haizhou Li
Recently, emotional speech synthesis has achieved remarkable performance. The emotion strength of synthesized speech can be controlled flexibly using a strength descriptor, which i…
PL-EESR: Perceptual Loss Based END-TO-END Robust Speaker Representation Extraction
Yi Ma, Kong Aik Lee, Ville Hautamaki +1
Speech enhancement aims to improve the perceptual quality of the speech signal by suppression of the background noise. However, excessive suppression may lead to speech distortion…
SLoClas: A Database for Joint Sound Localization and Classification
Xinyuan Qian, Bidisha Sharma, Amine El Abridi +1
In this work, we present the development of a new database, namely Sound Localization and Classification (SLoClas) corpus, for studying and analyzing sound localization and classif…
Serialized Multi-Layer Multi-Head Attention for Neural Speaker Embedding
Hongning Zhu, Kong Aik Lee, Haizhou Li
This paper proposes a serialized multi-layer multi-head attention for neural speaker embedding in text-independent speaker verification. In prior works, frame-level features from o…
Multi-Level Transfer Learning from Near-Field to Far-Field Speaker Verification
Li Zhang, Qing Wang, Kong Aik Lee +2
In far-field speaker verification, the performance of speaker embeddings is susceptible to degradation when there is a mismatch between the conditions of enrollment and test speech…
Multi-target DoA Estimation with an Audio-visual Fusion Mechanism
Xinyuan Qian, Maulik Madhavi, Zexu Pan +2
Most of the prior studies in the spatial \ac{DoA} domain focus on a single modality. However, humans use auditory and visual senses to detect the presence of sound sources. With th…
NHSS: A Speech and Singing Parallel Database
Bidisha Sharma, Xiaoxue Gao, Karthika Vijayan +2
We present a database of parallel recordings of speech and singing, collected and released by the Human Language Technology (HLT) laboratory at the National University of Singapore…
Optimizing voice conversion network with cycle consistency loss of speaker identity
Hongqiang Du, Xiaohai Tian, Lei Xie +1
We propose a novel training scheme to optimize voice conversion network with a speaker identity loss function. The training scheme not only minimizes frame-level spectral loss, but…
VAW-GAN for Disentanglement and Recomposition of Emotional Elements in Speech
Kun Zhou, Berrak Sisman, Haizhou Li
Emotional voice conversion (EVC) aims to convert the emotion of speech from one state to another while preserving the linguistic content and speaker identity. In this paper, we stu…
Seen and Unseen emotional style transfer for voice conversion with a new emotional speech dataset
Kun Zhou, Berrak Sisman, Rui Liu +1
Emotional voice conversion aims to transform emotional prosody in speech while preserving the linguistic content and speaker identity. Prior studies show that it is possible to dis…
Expressive TTS Training with Frame and Style Reconstruction Loss
Rui Liu, Berrak Sisman, Guanglai Gao +1
We propose a novel training strategy for Tacotron-based text-to-speech (TTS) system to improve the expressiveness of speech. One of the key challenges in prosody modeling is the la…
Converting Anyone's Emotion: Towards Speaker-Independent Emotional Voice Conversion
Kun Zhou, Berrak Sisman, Mingyang Zhang +1
Emotional voice conversion aims to convert the emotion of speech from one state to another while preserving the linguistic content and speaker identity. The prior studies on emotio…
The FFSVC 2020 Evaluation Plan
Xiaoyi Qin, Ming Li, Hui Bu +4
The Far-Field Speaker Verification Challenge 2020 (FFSVC20) is designed to boost the speaker verification research with special focus on far-field distributed microphone arrays und…
An efficient and perceptually motivated auditory neural encoding and decoding algorithm for spiking neural networks
Zihan Pan, Yansong Chua, Jibin Wu +3
Auditory front-end is an integral part of a spiking neural network (SNN) when performing auditory cognitive tasks. It encodes the temporal dynamic stimulus, such as speech and audi…