Sciweavers

ICASSP
2011
IEEE
13 years 2 months ago
Joint encoding of the waveform and speech recognition features using a transform codec
We propose a new transform speech codec that jointly encodes a wideband waveform and its corresponding wideband and narrowband speech recognition features. For distributed speech ...
Xing Fan, Michael L. Seltzer, Jasha Droppo, Henriq...
ICASSP
2011
IEEE
13 years 2 months ago
Survey and evaluation of acoustic features for speaker recognition
This study seeks to quantify the effectiveness of a broad range of acoustic features for speaker identification and their impact in feature fusion. Sixteen different acoustic feat...
Aaron D. Lawson, Pavel Vabishchevich, Mark C. Hugg...
ICASSP
2011
IEEE
13 years 2 months ago
Deep neural networks for acoustic emotion recognition: Raising the benchmarks
Deep Neural Networks (DNNs) denote multilayer artificial neural networks with more than one hidden layer and millions of free parameters. We propose a Generalized Discriminant An...
André Stuhlsatz, Christine Meyer, Florian E...
ICASSP
2011
IEEE
13 years 2 months ago
Bird species recognition combining acoustic and sequence modeling
The goal of this work was to explore modeling techniques to improve bird species classification from audio samples. We first developed an unsupervised approach to obtain approxima...
Martin Graciarena, Michelle Delplanche, Elizabeth ...
INTERSPEECH
2010
13 years 5 months ago
SCARF: a segmental conditional random field toolkit for speech recognition
This paper describes a new toolkit - SCARF - for doing speech recognition with segmental conditional random fields. It is designed to allow for the integration of numerous, possib...
Geoffrey Zweig, Patrick Nguyen
SIGDIAL
2010
13 years 8 months ago
Detection of time-pressure induced stress in speech via acoustic indicators
We use automatically extracted acoustic features to detect speech which is generated under stress, achieving 76.24% accuracy with a binary logistic regression. Our data are task-o...
Matthew Frampton, Sandeep Sripada, Ricardo Augusto...
CHI
2009
ACM
14 years 2 months ago
Comparing emotions using acoustics and human perceptual dimensions
Understanding the difference between emotions based on acoustic features is important for computer recognition and classification of emotions. We conducted a study of human percep...
Keshi Dai, Harriet J. Fell, Joel MacAuslan
ICASSP
2009
IEEE
14 years 2 months ago
Robust word boundary detection in spontaneous speech using acoustic and lexical cues
We consider the problem of word boundary detection in spontaneous speech utterances. Acoustic features have been well explored in the literature in the context of word boundary de...
Andreas Tsiartas, Prasanta K. Ghosh, Panayiotis G....
MIR
2010
ACM
217views Multimedia» more  MIR 2010»
14 years 4 months ago
Feature selection for content-based, time-varying musical emotion regression
In developing automated systems to recognize the emotional content of music, we are faced with a problem spanning two disparate domains: the space of human emotions and the acoust...
Erik M. Schmidt, Douglas Turnbull, Youngmoo E. Kim
SPEAKERC
2007
Springer
122views Biometrics» more  SPEAKERC 2007»
14 years 4 months ago
A Study of Acoustic Correlates of Speaker Age
Speaker age is a speaker characteristic which is always present in speech. Previous studies have found numerous acoustic features which correlate with speaker age. However, few att...
Susanne Schötz, Christian Müller