35 citations · 119 across the 22 of their papers we have counts for
22 papers
Cross-modal Alignment with Optimal Transport for CTC-based ASR
Xugang Lu, Peng Shen, Yu Tsao +1
Temporal connectionist temporal classification (CTC)-based automatic speech recognition (ASR) is one of the most successful end to end (E2E) ASR frameworks. However, due to the tok…
Pronunciation-aware unique character encoding for RNN Transducer-based Mandarin speech recognition
Peng Shen, Xugang Lu, Hisashi Kawai
For Mandarin end-to-end (E2E) automatic speech recognition (ASR) tasks, compared to character-based modeling units, pronunciation-based modeling units could improve the sharing of…
Speaking-Rate-Controllable HiFi-GAN Using Feature Interpolation
Detai Xin, Shinnosuke Takamichi, Takuma Okamoto +2
This paper presents a speaking-rate-controllable HiFi-GAN neural vocoder. Original HiFi-GAN is a high-fidelity, computationally efficient, and tiny-footprint neural vocoder. We att…
Transducer-based language embedding for spoken language identification
Peng Shen, Xugang Lu, Hisashi Kawai
The acoustic and linguistic features are important cues for the spoken language identification (LID) task. Recent advanced LID systems mainly use acoustic features that lack the us…
Partial Coupling of Optimal Transport for Spoken Language Identification
Xugang Lu, Peng Shen, Yu Tsao +1
In order to reduce domain discrepancy to improve the performance of cross-domain spoken language identification (SLID) system, as an unsupervised domain adaptation (UDA) method, we…
Siamese Neural Network with Joint Bayesian Model Structure for Speaker Verification
Xugang Lu, Peng Shen, Yu Tsao +1
Generative probability models are widely used for speaker verification (SV). However, the generative models are lack of discriminative feature selection ability. As a hypothesis te…
CrossMap Transformer: A Crossmodal Masked Path Transformer Using Double Back-Translation for Vision-and-Language Navigation
Aly Magassouba, Komei Sugiura, Hisashi Kawai
Navigation guided by natural language instructions is particularly suitable for Domestic Service Robots that interacts naturally with users. This task involves the prediction of a…
Predicting and Attending to Damaging Collisions for Placing Everyday Objects in Photo-Realistic Simulations
Aly Magassouba, Komei Sugiura, Angelica Nakayama +4
Placing objects is a fundamental task for domestic service robots (DSRs). Thus, inferring the collision-risk before a placing motion is crucial for achieving the requested task. Th…
Coupling a generative model with a discriminative learning framework for speaker verification
Xugang Lu, Peng Shen, Yu Tsao +1
The speaker verification (SV) task is to decide whether an utterance is spoken by a target or an imposter speaker. For most studies, a log-likelihood ratio (LLR) score is estimated…
Unsupervised neural adaptation model based on optimal transport for spoken language identification
Xugang Lu, Peng Shen, Yu Tsao +1
Due to the mismatch of statistical distributions of acoustic speech between training and testing sets, the performance of spoken language identification (SLID) could be drastically…
Alleviating the Burden of Labeling: Sentence Generation by Attention Branch Encoder-Decoder Network
Tadashi Ogura, Aly Magassouba, Komei Sugiura +4
Domestic service robots (DSRs) are a promising solution to the shortage of home care workers. However, one of the main limitations of DSRs is their inability to interact naturally…
Quasi-Periodic Parallel WaveGAN: A Non-autoregressive Raw Waveform Generative Model with Pitch-dependent Dilated Convolution Neural Network
Yi-Chiao Wu, Tomoki Hayashi, Takuma Okamoto +2
In this paper, we propose a quasi-periodic parallel WaveGAN (QPPWG) waveform generative model, which applies a quasi-periodic (QP) structure to a parallel WaveGAN (PWG) model using…
Quasi-Periodic Parallel WaveGAN Vocoder: A Non-autoregressive Pitch-dependent Dilated Convolution Model for Parametric Speech Generation
Yi-Chiao Wu, Tomoki Hayashi, Takuma Okamoto +2
In this paper, we propose a parallel WaveGAN (PWG)-like neural vocoder with a quasi-periodic (QP) architecture to improve the pitch controllability of PWG. PWG is a compact non-aut…
A Multimodal Target-Source Classifier with Attention Branches to Understand Ambiguous Instructions for Fetching Daily Objects
Aly Magassouba, Komei Sugiura, Hisashi Kawai
In this study, we focus on multimodal language understanding for fetching instructions in the domestic service robots context. This task consists of predicting a target object, as…
Cross-scale Attention Model for Acoustic Event Classification
Xugang Lu, Peng Shen, Sheng Li +2
A major advantage of a deep convolutional neural network (CNN) is that the focused receptive field size is increased by stacking multiple convolutional layers. Accordingly, the mod…
Multimodal Attention Branch Network for Perspective-Free Sentence Generation
Aly Magassouba, Komei Sugiura, Hisashi Kawai
In this paper, we address the automatic sentence generation of fetching instructions for domestic service robots. Typical fetching commands such as "bring me the yellow toy from th…
Understanding Natural Language Instructions for Fetching Daily Objects Using GAN-Based Multimodal Target-Source Classification
Aly Magassouba, Komei Sugiura, Anh Trinh Quoc +1
In this paper, we address multimodal language understanding for unconstrained fetching instruction in domestic service robots context. A typical fetching instruction such as "Bring…
Incorporating Symbolic Sequential Modeling for Speech Enhancement
Chien-Feng Liao, Yu Tsao, Xugang Lu +1
In a noisy environment, a lossy speech signal can be automatically restored by a listener if he/she knows the language well. That is, with the built-in knowledge of a "language mod…
A Multimodal Classifier Generative Adversarial Network for Carry and Place Tasks from Ambiguous Language Instructions
Aly Magassouba, Komei Sugiura, Hisashi Kawai
This paper focuses on a multimodal language understanding method for carry-and-place tasks with domestic service robots. We address the case of ambiguous instructions, that is, whe…
Grounded Language Understanding for Manipulation Instructions Using GAN-Based Classification
Komei Sugiura, Hisashi Kawai
The target task of this study is grounded language understanding for domestic service robots (DSRs). In particular, we focus on instruction understanding for short sentences where…
End-to-End Waveform Utterance Enhancement for Direct Evaluation Metrics Optimization by Fully Convolutional Neural Networks
Szu-Wei Fu, Tao-Wei Wang, Yu Tsao +2
Speech enhancement model is used to map a noisy speech to a clean speech. In the training stage, an objective function is often adopted to optimize the model parameters. However, i…
Raw Waveform-based Speech Enhancement by Fully Convolutional Networks
Szu-Wei Fu, Yu Tsao, Xugang Lu +1
This study proposes a fully convolutional network (FCN) model for raw waveform-based speech enhancement. The proposed system performs speech enhancement in an end-to-end (i.e., wav…