---
title: "Interspeech 2013 — accepted papers — Elamur Research"
description: "Interspeech 2013 — accepted papers: 1 paper in the Elamur Research library, with our summaries, ranked by citations."
canonical: "https://research.elamur.ai/free/en/venues/interspeech-usb/2013/"
---
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[home](https://md.research.elamur.ai/free/en/) / [venues](https://md.research.elamur.ai/free/en/venues/) / [Interspeech](https://md.research.elamur.ai/free/en/venues/interspeech-usb/) / 2013

# Interspeech 2013 — accepted papers

Interspeech 2013 is the 2013 edition of the Interspeech. OpenAlex lists 747 papers of it; our library holds 1 with our summaries. Below: the most cited papers, every accepted paper, and ours with their topics, authors and institutions.

[**747** papers in the proceedings](#all) · [**1** work in our library](https://md.research.elamur.ai/free/en/venues/interspeech-usb/2013/#works) · [**949** citations of these works](https://md.research.elamur.ai/free/en/venues/interspeech-usb/2013/#works)

## Most cited papers

By their OpenAlex citations; a paper with our summary links to its page here, the others to the original.

1. **[Speech enhancement based on deep denoising autoencoder ↗](https://doi.org/10.21437/interspeech.2013-130)**Xugang Lu, Yu Tsao, Shigeki Matsuda et al.*834 citations*
2. **[The INTERSPEECH 2013 computational paralinguistics challenge: social signals, conflict, emotion, autism ↗](https://doi.org/10.21437/interspeech.2013-56)**Björn Wolfgang Schuller, Stefan Steidl, Anton M. Batliner et al.*731 citations*
3. **[Sequence-discriminative training of deep neural networks ↗](https://doi.org/10.21437/interspeech.2013-548)**Karel Veselý, Arnab Kumar Ghoshal, Lukáš Burget et al.*657 citations*
4. **[Investigation of recurrent-neural-network architectures and learning methods for spoken language understanding ↗](https://doi.org/10.21437/interspeech.2013-596)**Grégoire Mesnil, Xiaodong He, Li Deng et al.*413 citations*
5. **[Restructuring of deep neural network acoustic models with singular value decomposition ↗](https://doi.org/10.21437/interspeech.2013-552)**Jian Xue, Jinyu Li, Yifan Gong*407 citations*
6. **[Exploring convolutional neural network structures and optimization techniques for speech recognition ↗](https://doi.org/10.21437/interspeech.2013-744)**Ossama Abdel‐Hamid, Li Deng, Dong Yu*384 citations*
7. **[Recurrent neural networks for language understanding ↗](https://doi.org/10.21437/interspeech.2013-569)**Kaisheng Yao, Geoffrey Zweig, Mei-Yuh Hwang et al.*315 citations*
8. **[Cross-entropy vs. squared error training: a theoretical and experimental comparison ↗](https://doi.org/10.21437/interspeech.2013-436)**Pavel Golik, Patrick Doetsch, Hermann Ney*220 citations*
9. **[Improved feature processing for deep neural networks ↗](https://doi.org/10.21437/interspeech.2013-48)**Shakti P. Rath, Daniel Povey, Karel Veselý et al.*187 citations*
10. **[Estimating phoneme class conditional probabilities from raw speech signal using convolutional neural networks ↗](https://doi.org/10.21437/interspeech.2013-438)**Dimitri Palaz, Ronan Collobert, Mathew Magimai.-Doss*185 citations*

## All accepted papers (747)

The most cited first; 1 with our summary link to their page here, the others to the original.

1. **[Speech enhancement based on deep denoising autoencoder ↗](https://doi.org/10.21437/interspeech.2013-130)**Xugang Lu, Yu Tsao, Shigeki Matsuda et al.*834 citations*
2. **[The INTERSPEECH 2013 computational paralinguistics challenge: social signals, conflict, emotion, autism ↗](https://doi.org/10.21437/interspeech.2013-56)**Björn Wolfgang Schuller, Stefan Steidl, Anton M. Batliner et al.*731 citations*
3. **[Sequence-discriminative training of deep neural networks ↗](https://doi.org/10.21437/interspeech.2013-548)**Karel Veselý, Arnab Kumar Ghoshal, Lukáš Burget et al.*657 citations*
4. **[Investigation of recurrent-neural-network architectures and learning methods for spoken language understanding ↗](https://doi.org/10.21437/interspeech.2013-596)**Grégoire Mesnil, Xiaodong He, Li Deng et al.*413 citations*
5. **[Restructuring of deep neural network acoustic models with singular value decomposition ↗](https://doi.org/10.21437/interspeech.2013-552)**Jian Xue, Jinyu Li, Yifan Gong*407 citations*
6. **[Exploring convolutional neural network structures and optimization techniques for speech recognition ↗](https://doi.org/10.21437/interspeech.2013-744)**Ossama Abdel‐Hamid, Li Deng, Dong Yu*384 citations*
7. **[Recurrent neural networks for language understanding ↗](https://doi.org/10.21437/interspeech.2013-569)**Kaisheng Yao, Geoffrey Zweig, Mei-Yuh Hwang et al.*315 citations*
8. **[Cross-entropy vs. squared error training: a theoretical and experimental comparison ↗](https://doi.org/10.21437/interspeech.2013-436)**Pavel Golik, Patrick Doetsch, Hermann Ney*220 citations*
9. **[Improved feature processing for deep neural networks ↗](https://doi.org/10.21437/interspeech.2013-48)**Shakti P. Rath, Daniel Povey, Karel Veselý et al.*187 citations*
10. **[Estimating phoneme class conditional probabilities from raw speech signal using convolutional neural networks ↗](https://doi.org/10.21437/interspeech.2013-438)**Dimitri Palaz, Ronan Collobert, Mathew Magimai.-Doss*185 citations*
11. **[Spoofing and countermeasures for automatic speaker verification ↗](https://doi.org/10.21437/interspeech.2013-288)**Nicholas Evans, Tomi Kinnunen, Junichi Yamagishi*160 citations*
12. **[Investigating voice quality as a speaker-independent indicator of depression and PTSD ↗](https://doi.org/10.21437/interspeech.2013-240)**Stefan J. Scherer, Giota Stratou, Jonathan S. Gratch et al.*137 citations*
13. **[Evaluating speech features with the minimal-pair ABX task: analysis of the classical MFC/PLP pipeline ↗](https://doi.org/10.21437/interspeech.2013-441)**Thomas Schatz, Vijayaditya Peddinti, Francis Bach et al.*134 citations*
14. **[An open-source state-of-the-art toolbox for broadcast news diarization ↗](https://doi.org/10.21437/interspeech.2013-383)**Mickaël Rouvier, Grégor Dupuy, Paul Gay et al.*124 citations*
15. **[Voice conversion in high-order eigen space using deep belief nets ↗](https://doi.org/10.21437/interspeech.2013-102)**Toru Nakashika, Ryoichi Takashima, Tetsuya Takiguchi et al.*121 citations*
16. **[Accurate and compact large vocabulary speech recognition on mobile devices ↗](https://doi.org/10.21437/interspeech.2013-189)**Xin Lei, Andrew Senior, Alexander Gruenstein et al.*119 citations*
17. **[Speech activity detection on youtube using deep neural networks ↗](https://doi.org/10.21437/interspeech.2013-203)**Neville Ryant, Mark Liberman, Jiahong Yuan*101 citations*
18. **[ALIZE 3.0 — open source toolkit for state-of-the-art speaker recognition ↗](https://doi.org/10.21437/interspeech.2013-634)**Anthony Larcher, Jean-François Bonastre, Benoît Fauve et al.*98 citations*
19. **[I-vectors meet imitators: on vulnerability of speaker verification systems against voice mimicry ↗](https://doi.org/10.21437/interspeech.2013-289)**Rosa González Hautamäki, Tomi Kinnunen, Ville Hautamäki et al.*95 citations*
20. **[Reverberant speech recognition based on denoising autoencoder ↗](https://doi.org/10.21437/interspeech.2013-267)**Takaaki Ishii, Hiroki Komiyama, Takahiro Shinozaki et al.*90 citations*
21. **[Convergence of articulation rate in spontaneous speech ↗](https://doi.org/10.21437/interspeech.2013-148)**Antje Schweitzer, Natalie Lewandowski*87 citations*
22. **[A new DNN-based high quality pronunciation evaluation for computer-aided language learning (CALL) ↗](https://doi.org/10.21437/interspeech.2013-458)**Wenping Hu, Yao Qian, Frank K. Soong*78 citations*
23. **[Evaluation of speech-based protocol for detection of early-stage dementia ↗](https://doi.org/10.21437/interspeech.2013-32)**Aharon Satt, Alexander S. Sorin, Orith Ronen et al.*77 citations*
24. **[Improvement of distant-talking speaker identification using bottleneck features of DNN ↗](https://doi.org/10.21437/interspeech.2013-686)**Takanori Yamada, Longbiao Wang, Atsuhiko Kai*72 citations*
25. **[I4u submission to NIST SRE 2012: a large-scale collaborative effort for noise-robust speaker verification ↗](https://doi.org/10.21437/interspeech.2013-472)**Haizhou Li, John H. L. Hansen, Jean-François Bonastre et al.*71 citations*

[See all 747 papers in Interspeech 2013 — accepted papers →](https://md.research.elamur.ai/free/en/venues/interspeech-usb/2013/papers/)

## Papers with our summary in our library (1)

The most cited first (OpenAlex citations plus our library's).

1. **[One Billion Word Benchmark for Measuring Progress in Statistical Language Modeling](https://md.research.elamur.ai/free/en/papers/chelba-2013-one-billion-word-benchmark-measuring/) [Interspeech](https://md.research.elamur.ai/free/en/venues/interspeech-usb/)**Ciprian Chelba, Tomas Mikolov, Mike Schuster, et al.*2013 · 949 citations*

## Top topics

Topics of its works in our library, with the number of works on each.

[Language models & pretraining (1)](https://md.research.elamur.ai/free/en/topics/language-models/) · [Evaluation & benchmarks (1)](https://md.research.elamur.ai/free/en/topics/evaluation-benchmarks/)

## Fields

[Arts and Humanities (1)](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Computer Science (1)](https://md.research.elamur.ai/free/en/shelves/computer-science/)

## Top authors

Authors with a page who published here most often: their works here, and the citations of those works.

[🧑‍🔬**Ciprian Chelba**1 work here · 949 citations](https://md.research.elamur.ai/free/en/authors/ciprian-chelba/) · [🧑‍🔬**Mike Schuster**1 work here · 949 citations](https://md.research.elamur.ai/free/en/authors/mike-schuster/) · [🧑‍🔬**Thorsten Brants**1 work here · 949 citations](https://md.research.elamur.ai/free/en/authors/thorsten-brants/) · [🧑‍🔬**Tomas Mikolov**1 work here · 949 citations](https://md.research.elamur.ai/free/en/authors/tomas-mikolov/)

## Top institutions

Institutions on the bylines of its works here, by the number of works.

[🏢**Google** Mountain View · United States 1 work here](https://md.research.elamur.ai/free/en/companies/google/)

works and citations from OpenAlex and our library.

- [next → Interspeech 2015](https://md.research.elamur.ai/free/en/venues/interspeech-usb/2015/)
- [↑ back to Interspeech](https://md.research.elamur.ai/free/en/venues/interspeech-usb/)