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Advances in Speech and Language Technologies for Iberian Languages

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Cover of 'Advances in Speech and Language Technologies for Iberian Languages'

Table of Contents

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    Book Overview
  2. Altmetric Badge
    Chapter 1 Study of the Effect of Reducing Training Data in Speech Synthesis Adaptation Based on Frequency Warping
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    Chapter 2 A Dynamic FEC for Improved Robustness of CELP-Based Codec
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    Chapter 3 Objective Comparison of Four GMM-Based Methods for PMA-to-Speech Conversion
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    Chapter 4 Adding Singing Capabilities to Unit Selection TTS Through HNM-Based Conversion
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    Chapter 5 A Novel Error Mitigation Scheme Based on Replacement Vectors and FEC Codes for Speech Recovery in Loss-Prone Channels
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    Chapter 6 Language-Independent Acoustic Cloning of HTS Voices: An Objective Evaluation
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    Chapter 7 Prosodic Break Prediction with RNNs
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    Chapter 8 Surgery of Speech Synthesis Models to Overcome the Scarcity of Training Data
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    Chapter 9 An Analysis of Deep Neural Networks in Broad Phonetic Classes for Noisy Speech Recognition
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    Chapter 10 Automatic Speech Recognition with Deep Neural Networks for Impaired Speech
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    Chapter 11 Detection of Publicity Mentions in Broadcast Radio: Preliminary Results
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    Chapter 12 Deep Neural Network-Based Noise Estimation for Robust ASR in Dual-Microphone Smartphones
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    Chapter 13 Better Phoneme Recognisers Lead to Better Phoneme Posteriorgrams for Search on Speech? An Experimental Analysis
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    Chapter 14 Crowdsourced Video Subtitling with Adaptation Based on User-Corrected Lattices
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    Chapter 15 Acoustic Analysis of Anomalous Use of Prosodic Features in a Corpus of People with Intellectual Disability
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    Chapter 16 Detecting Psychological Distress in Adults Through Transcriptions of Clinical Interviews
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    Chapter 17 Automatic Annotation of Disfluent Speech in Children’s Reading Tasks
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    Chapter 18 Automatic Detection of Hyperarticulated Speech
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    Chapter 19 Acoustic-Prosodic Automatic Personality Trait Assessment for Adults and Children
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    Chapter 20 Evaluating Different Non-native Pronunciation Scoring Metrics with the Japanese Speakers of the SAMPLE Corpus
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    Chapter 21 Global Analysis of Entrainment in Dialogues
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    Chapter 22 A Train-on-Target Strategy for Multilingual Spoken Language Understanding
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    Chapter 23 Collaborator Effort Optimisation in Multimodal Crowdsourcing for Transcribing Historical Manuscripts
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    Chapter 24 Assessing User Expertise in Spoken Dialog System Interactions
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    Chapter 25 Automatic Speech Feature Learning for Continuous Prediction of Customer Satisfaction in Contact Center Phone Calls
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    Chapter 26 Reversible Speech De-identification Using Parametric Transformations and Watermarking
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    Chapter 27 Bottleneck Based Front-End for Diarization Systems
Attention for Chapter 10: Automatic Speech Recognition with Deep Neural Networks for Impaired Speech
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Chapter title
Automatic Speech Recognition with Deep Neural Networks for Impaired Speech
Chapter number 10
Book title
Advances in Speech and Language Technologies for Iberian Languages
Published in
Lecture notes in computer science, November 2016
DOI 10.1007/978-3-319-49169-1_10
Book ISBNs
978-3-31-949168-4, 978-3-31-949169-1
Authors

Cristina España-Bonet, José A. R. Fonollosa, España-i-Bonet, Cristina, Rodríguez Fonollosa, José Adrián

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 29 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 29 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 21%
Student > Bachelor 3 10%
Lecturer > Senior Lecturer 2 7%
Lecturer 2 7%
Student > Master 2 7%
Other 3 10%
Unknown 11 38%
Readers by discipline Count As %
Computer Science 10 34%
Engineering 5 17%
Linguistics 1 3%
Unknown 13 45%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 28 April 2017.
All research outputs
#20,414,746
of 22,965,074 outputs
Outputs from Lecture notes in computer science
#7,006
of 8,137 outputs
Outputs of similar age
#269,415
of 311,790 outputs
Outputs of similar age from Lecture notes in computer science
#317
of 364 outputs
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So far Altmetric has tracked 8,137 research outputs from this source. They receive a mean Attention Score of 5.0. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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We're also able to compare this research output to 364 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.