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2015 IEEE Workshop on Automatic Speech Recognition and Understanding (ASRU)

Organizing committee

Table of contents

Different word representations and their combination for proper name retrieval from diachronic documents

Sparse non-negative matrix language modeling for geo-annotated query session data

Training data pseudo-shuffling and direct decoding framework for recurrent neural network based acoustic modeling

On constructing and analysing an interpretable brain model for the DNN based on hidden activity patterns

Speaker location and microphone spacing invariant acoustic modeling from raw multichannel waveforms

Hybrid DNN-Latent structured SVM acoustic models for continuous speech recognition

Discriminative training of context-dependent language model scaling factors and interpolation weights

Acoustic model training based on node-wise weight boundary model increasing speed of discrete neural networks

Two-stage ASGD framework for parallel training of DNN acoustic models using Ethernet

RNNDROP: A novel dropout for RNNS in ASR

Spectral learning with non negative probabilities for finite state automaton

Deep bi-directional recurrent networks over spectral windows

Personalizing universal recurrent neural network language model with user characteristic features by social network crowdsourcing

Time delay deep neural network-based universal background models for speaker recognition

Automatic prosody prediction for Chinese speech synthesis using BLSTM-RNN and embedding features

Naturalness and rapport in a pitch adaptive learning companion

Learning continuous representation of text for phone duration modeling in statistical parametric speech synthesis

Speaker intonation adaptation for transforming text-to-speech synthesis speaker identity

Investigating sparse deep neural networks for speech recognition

Latent Dirichlet Allocation based organisation of broadcast media archives for deep neural network adaptation

Towards structured deep neural network for automatic speech recognition

Learning factorized feature transforms for speaker normalization

Improving data selection for low-resource STT and KWS

Structured discriminative models using deep neural-network features

EESEN: End-to-end speech recognition using deep RNN models and WFST-based decoding

Stochastic Gradient Variational Bayes for deep learning-based ASR

Investigation of back-off based interpolation between recurrent neural network and n-gram language models

LSTM time and frequency recurrence for automatic speech recognition

Incorporating user feedback to re-rank keyword search results

Combination of syllable based N-gram search and word search for spoken term detection through spoken queries and IV/OOV classification

Incorporating paragraph embeddings and density peaks clustering for spoken document summarization

High-performance Swahili keyword search with very limited language pack: The THUEE system for the OpenKWS15 evaluation

Phonetic unit selection for cross-lingual query-by-example spoken term detection

Improved system fusion for keyword search

Deep multimodal semantic embeddings for speech and images

An iterative deep learning framework for unsupervised discovery of speech features and linguistic units with applications on spoken term detection

Incremental sentence compression using LSTM recurrent networks

Multilingual representations for low resource speech recognition and keyword search

Spoken language translation graphs re-decoding using automatic quality assessment

The DIRHA-ENGLISH corpus and related tasks for distant-speech recognition in domestic environments

Uncertainty estimation of DNN classifiers

Towards utterance-based neural network adaptation in acoustic modeling

Phonetically-oriented word error alignment for speech recognition error analysis in speech translation

Utterance classification in speech-to-speech translation for zero-resource languages in the hospital administration domain

Multi-task joint-learning of deep neural networks for robust speech recognition

Time-frequency convolutional networks for robust speech recognition

Name-aware language model adaptation and sparse features for statistical machine translation

An i-Vector PLDA based gender identification approach for severely distorted and multilingual DARPA RATS data

Using bidirectional lstm recurrent neural networks to learn high-level abstractions of sequential features for automated scoring of non-native spontaneous speech

Topic-space based setup of a neural network for theme identification of highly imperfect transcriptions

Semi-supervised slot tagging in spoken language understanding using recurrent transductive support vector machines

A universal model for flexible item selection in conversational dialogs

A comparative study of neural network models for lexical intent classification

Detecting actionable items in meetings by convolutional deep structured semantic models

Multimodal embedding fusion for robust speaker role recognition in video broadcast

Recent improvements to NeuroCRFs for named entity recognition

Natural language understanding for partial queries

Adaptive beamforming and adaptive training of DNN acoustic models for enhanced multichannel noisy speech recognition

Boosted acoustic model learning and hypotheses rescoring on the CHiME-3 task

Unified ASR system using LGM-based source separation, noise-robust feature extraction, and word hypothesis selection

Speech enhancement using beamforming and non negative matrix factorization for robust speech recognition in the CHiME-3 challenge

An information fusion approach to recognizing microphone array speech in the CHiME-3 challenge based on a deep learning framework

The NTT CHiME-3 system: Advances in speech enhancement and recognition for mobile multi-microphone devices

BLSTM supported GEV beamformer front-end for the 3RD CHiME challenge

Multi-channel speech processing architectures for noise robust speech recognition: 3rd CHiME challenge results

Robust speech recognition using beamforming with adaptive microphone gains and multichannel noise reduction

A CHiME-3 challenge system: Long-term acoustic features for noise robust automatic speech recognition

The MERL/SRI system for the 3RD CHiME challenge using beamforming, robust feature extraction, and advanced speech recognition

Robust ASR using neural network based speech enhancement and feature simulation

Exploiting synchrony spectra and deep neural networks for noise-robust automatic speech recognition

Combining spectral feature mapping and multi-channel model-based source separation for noise-robust automatic speech recognition

The third ‘CHiME’ speech separation and recognition challenge: Dataset, task and baselines

Analysis of factors affecting system performance in the ASpIRE challenge

Single and multi-channel approaches for distant speech recognition under noisy reverberant conditions: I2R'S system description for the ASpIRE challenge

Improving robustness against reverberation for automatic speech recognition

Robust speech recognition in unknown reverberant and noisy conditions

JHU ASpIRE system: Robust LVCSR with TDNNS, iVector adaptation and RNN-LMS

The Automatic Speech recogition In Reverberant Environments (ASpIRE) challenge

Deep bottleneck features for i-vector based text-independent speaker verification

Discriminative segmental cascades for feature-rich phone recognition

Hilbert spectral analysis of vowels using intrinsic mode functions

Multi-reference WER for evaluating ASR for languages with no orthographic rules

Acoustic modeling with neural graph embeddings

Multitask learning and system combination for automatic speech recognition

Speaker adaptive joint training of Gaussian mixture models and bottleneck features

Acoustic modelling with CD-CTC-SMBR LSTM RNNS

Automation of system building for state-of-the-art large vocabulary speech recognition using evolution strategy

Improving the interpretability of deep neural networks with stimulated learning

The 2015 sheffield system for transcription of Multi-Genre Broadcast media

The 2015 sheffield system for longitudinal diarisation of broadcast media

Cambridge university transcription systems for the multi-genre broadcast challenge

The development of the cambridge university alignment systems for the multi-genre broadcast challenge

The NAIST ASR system for the 2015 Multi-Genre Broadcast challenge: On combination of deep learning systems using a rank-score function

Speaker diarisation and longitudinal linking in multi-genre broadcast data

Variational Bayesian PLDA for speaker diarization in the MGB challenge

A system for automatic alignment of broadcast media captions using weighted finite-state transducers

CRIM and LIUM approaches for multi-genre broadcast media transcription

The MGB challenge: Evaluating multi-genre broadcast media recognition

Incremental LSTM-based dialog state tracker

Multi-domain dialogue success classifiers for policy training

Open-domain personalized dialog system using user-interested topics in system responses

A study of social-affective communication: Automatic prediction of emotion triggers and responses in television talk shows

Adaptive selection from multiple response candidates in example-based dialogue

Optimizing human-interpretable dialog management policy using genetic algorithm

Implementation of generic positive-negative tracker in extensible dialog system

Policy committee for adaptation in multi-domain spoken dialogue systems

Applying deep learning to answer selection: A study and an open task

2013 IEEE Workshop on Automatic Speech Recognition and Understanding

2011 IEEE Workshop on Automatic Speech Recognition & Understanding

2009 IEEE Workshop on Automatic Speech Recognition & Understanding

2007 IEEE Workshop on Automatic Speech Recognition & Understanding (ASRU)

IEEE Workshop on Automatic Speech Recognition and Understanding, 2005.

2003 IEEE Workshop on Automatic Speech Recognition and Understanding (IEEE Cat. No.03EX721)

IEEE Workshop on Automatic Speech Recognition and Understanding, 2001. ASRU '01.

1997 IEEE Workshop on Automatic Speech Recognition and Understanding Proceedings

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