Search Results for author:
Found 55 papers, 12 papers with code
An Attentive Listening System with Android ERICA: Comparison of Autonomous and WOZ Interactions
The proposed system generates several types of listener responses: backchannels, repeats, elaborating questions, assessments, generic sentimental responses, and generic responses.
A multi-party attentive listening robot which stimulates involvement from side participants
We demonstrate the moderating abilities of a multi-party attentive listening robot system when multiple people are speaking in turns.
Simultaneous Job Interview System Using Multiple Semi-autonomous Agents
We propose a simultaneous job interview system, where one interviewer can conduct one-on-one interviews with multiple applicants simultaneously by cooperating with the multiple autonomous job interview dialogue systems.
Multilingual Turn-taking Prediction Using Voice Activity Projection
The results show that a monolingual VAP model trained on one language does not make good predictions when applied to other languages.
Investigation of Adapter for Automatic Speech Recognition in Noisy Environment
Adapting an automatic speech recognition (ASR) system to unseen noise environments is crucial.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
Evaluation of a semi-autonomous attentive listening system with takeover prompting
To this end, we propose a semi-autonomous system, where a remote operator can take control of an autonomous attentive listening system in real-time.
Acknowledgment of Emotional States: Generating Validating Responses for Empathetic Dialogue
This study introduces the first framework designed to engender empathetic dialogue with validating responses.
MOS-FAD: Improving Fake Audio Detection Via Automatic Mean Opinion Score Prediction
We propose MOS-FAD, where MOS can be leveraged at two key points in FAD: training data selection and model fusion.
Enhancing Personality Recognition in Dialogue by Data Augmentation and Heterogeneous Conversational Graph Networks
Personality recognition is useful for enhancing robots' ability to tailor user-adaptive responses, thus fostering rich human-robot interactions.
Real-time and Continuous Turn-taking Prediction Using Voice Activity Projection
A demonstration of a real-time and continuous turn-taking prediction system is presented.
An Analysis of User Behaviors for Objectively Evaluating Spoken Dialogue Systems
To address this issue, we propose a framework for indirectly but objectively evaluating systems based on users' behaviors.
Towards Objective Evaluation of Socially-Situated Conversational Robots: Assessing Human-Likeness through Multimodal User Behaviors
This paper tackles the challenging task of evaluating socially situated conversational robots and presents a novel objective evaluation approach that relies on multimodal user behaviors.
Reasoning before Responding: Integrating Commonsense-based Causality Explanation for Empathetic Response Generation
We enhance ChatGPT's ability to reason for the system's perspective by integrating in-context learning with commonsense knowledge.
Diffusion-Based Speech Enhancement with Joint Generative and Predictive Decoders
At the decoded feature level, we fuse the two decoded features by generative and predictive decoders.
Non-autoregressive Error Correction for CTC-based ASR with Phone-conditioned Masked LM
Connectionist temporal classification (CTC) -based models are attractive in automatic speech recognition (ASR) because of their non-autoregressive nature.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
Distilling the Knowledge of BERT for CTC-based ASR
In this study, we propose to distill the knowledge of BERT for CTC-based ASR, extending our previous study for attention-based ASR.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
End-to-end Speech-to-Punctuated-Text Recognition
We also propose to incorporate an auxiliary loss to train the model using the output of the intermediate layer and unpunctuated texts.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
ASR Rescoring and Confidence Estimation with ELECTRA
We propose an ASR rescoring method for directly detecting errors with ELECTRA, which is originally a pre-training method for NLP tasks.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Non-autoregressive End-to-end Speech Translation with Parallel Autoregressive Rescoring
We propose a unified NAR E2E-ST framework called Orthros, which has an NAR decoder and an auxiliary shallow AR decoder on top of the shared encoder.
VAD-free Streaming Hybrid CTC/Attention ASR for Unsegmented Recording
In this work, we propose novel decoding algorithms to enable streaming automatic speech recognition (ASR) on unsegmented long-form recordings without voice activity detection (VAD), based on monotonic chunkwise attention (MoChA) with an auxiliary connectionist temporal classification (CTC) objective.
StableEmit: Selection Probability Discount for Reducing Emission Latency of Streaming Monotonic Attention ASR
Previous works tackled this problem by leveraging alignment information to control the timing to emit tokens during training.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
ERICA: An Empathetic Android Companion for Covid-19 Quarantine
Over the past year, research in various domains, including Natural Language Processing (NLP), has been accelerated to fight against the COVID-19 pandemic, yet such research has just started on dialogue systems.
Intelligent Conversational Android ERICA Applied to Attentive Listening and Job Interview
It has also been evaluated with student subjects, showing promising results.
Source and Target Bidirectional Knowledge Distillation for End-to-end Speech Translation
To leverage the full potential of the source language information, we propose backward SeqKD, SeqKD from a target-to-source backward NMT model.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+5
Alignment Knowledge Distillation for Online Streaming Attention-based Speech Recognition
We compare CTC-ST with several methods that distill alignment knowledge from a hybrid ASR system and show that the CTC-ST can achieve a comparable tradeoff of accuracy and latency without relying on external alignment information.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Topic-relevant Response Generation using Optimal Transport for an Open-domain Dialog System
The semantic constraint, which encourages a response to be semantically related to its context by regularizing the decoding objective function with semantic distance, is proposed.
Orthros: Non-autoregressive End-to-end Speech Translation with Dual-decoder
Fast inference speed is an important goal towards real-world deployment of speech translation (ST) systems.
Multi-Referenced Training for Dialogue Response Generation
In this work, we first analyze the training objective of dialogue models from the view of Kullback-Leibler divergence (KLD) and show that the gap between the real world probability distribution and the single-referenced data's probability distribution prevents the model from learning the one-to-many relations efficiently.
End-to-end Music-mixed Speech Recognition
The time-domain separation method outperformed a frequency-domain separation method, which reuses the phase information of the input mixture signal, both in simple cascading and joint training settings.
Audio and Speech Processing
Distilling the Knowledge of BERT for Sequence-to-Sequence ASR
Experimental evaluations show that our method significantly improves the ASR performance from the seq2seq baseline on the Corpus of Spontaneous Japanese (CSJ).
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
Generative Adversarial Training Data Adaptation for Very Low-resource Automatic Speech Recognition
We evaluated this speaker adaptation approach on two low-resource corpora, namely, Ainu and Mboshi.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
Enhancing Monotonic Multihead Attention for Streaming ASR
For streaming inference, all monotonic attention (MA) heads should learn proper alignments because the next token is not generated until all heads detect the corresponding token boundaries.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
CTC-synchronous Training for Monotonic Attention Model
Monotonic chunkwise attention (MoChA) has been studied for the online streaming automatic speech recognition (ASR) based on a sequence-to-sequence framework.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
End-to-end speech-to-dialog-act recognition
In the proposed model, the dialog act recognition network is conjunct with an acoustic-to-word ASR model at its latent layer before the softmax layer, which provides a distributed representation of word-level ASR decoding information.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Designing Precise and Robust Dialogue Response Evaluators
Automatic dialogue response evaluator has been proposed as an alternative to automated metrics and human evaluation.
Speech Corpus of Ainu Folklore and End-to-end Speech Recognition for Ainu Language
Ainu is an unwritten language that has been spoken by Ainu people who are one of the ethnic groups in Japan.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Semi-Supervised Multichannel Speech Enhancement With a Deep Speech Prior
To solve this problem, we replace a low-rank speech model with a deep generative speech model, i. e., formulate a probabilistic model of noisy speech by integrating a deep speech model, a low-rank noise model, and a full-rank or rank-1 model of spatial characteristics of speech and noise.
Multilingual End-to-End Speech Translation
In this paper, we propose a simple yet effective framework for multilingual end-to-end speech translation (ST), in which speech utterances in source languages are directly translated to the desired target languages with a universal sequence-to-sequence architecture.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+4
Improving OOV Detection and Resolution with External Language Models in Acoustic-to-Word ASR
Moreover, the A2C model can be used to recover out-of-vocabulary (OOV) words that are not covered by the A2W model, but this requires accurate detection of OOV words.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
Effective Incorporation of Speaker Information in Utterance Encoding in Dialog
In dialog studies, we often encode a dialog using a hierarchical encoder where each utterance is converted into an utterance vector, and then a sequence of utterance vectors is converted into a dialog vector.
Content Word-based Sentence Decoding and Evaluating for Open-domain Neural Response Generation
Various encoder-decoder models have been applied to response generation in open-domain dialogs, but a majority of conventional models directly learn a mapping from lexical input to lexical output without explicitly modeling intermediate representations.
Unsupervised Speech Enhancement Based on Multichannel NMF-Informed Beamforming for Noise-Robust Automatic Speech Recognition
To solve this problem, we take an unsupervised approach that decomposes each TF bin into the sum of speech and noise by using multichannel nonnegative matrix factorization (MNMF).
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Transfer learning of language-independent end-to-end ASR with language model fusion
This work explores better adaptation methods to low-resource languages using an external language model (LM) under the framework of transfer learning.
A Unified Neural Architecture for Joint Dialog Act Segmentation and Recognition in Spoken Dialog System
We propose a unified architecture based on neural networks, which consists of a sequence tagger for segmentation and a classifier for recognition.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+5
Joint Learning of Dialog Act Segmentation and Recognition in Spoken Dialog Using Neural Networks
Dialog act segmentation and recognition are basic natural language understanding tasks in spoken dialog systems.
Automatic Speech Recognition (ASR)
Natural Language Understanding
+2
Statistical Speech Enhancement Based on Probabilistic Integration of Variational Autoencoder and Non-Negative Matrix Factorization
This paper presents a statistical method of single-channel speech enhancement that uses a variational autoencoder (VAE) as a prior distribution on clean speech.
Attentive listening system with backchanneling, response generation and flexible turn-taking
Second, we propose an effective statement response mechanism which detects focus words and responds in the form of a question or partial repeat.
Automatic Speech Recognition Errors as a Predictor of L2 Listening Difficulties
To improve the choice of words in this system, and explore a better method to detect speech challenges, ASR errors were investigated as a model of the L2 listener, hypothesizing that some of these errors are similar to those of language learners{'} when transcribing the videos.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Designing an Evaluation Framework for Spoken Term Detection and Spoken Document Retrieval at the NTCIR-9 SpokenDoc Task
We describe the evaluation framework for spoken document retrieval for the IR for the Spoken Documents Task, conducted in the ninth NTCIR Workshop.
