41,363 research outputs found
Exploring Non-linear Transformations for an Entropybased Voice Activity Detector
In this paper we explore the use of non-linear transformations in
order to improve the performance of an entropy based voice activity detector
(VAD). The idea of using a non-linear transformation comes from some
previous work done in speech linear prediction (LPC) field based in source
separation techniques, where the score function was added into the classical
equations in order to take into account the real distribution of the signal. We
explore the possibility of estimating the entropy of frames after calculating its
score function, instead of using original frames. We observe that if signal is
clean, estimated entropy is essentially the same; but if signal is noisy
transformed frames (with score function) are able to give different entropy if
the frame is voiced against unvoiced ones. Experimental results show that this
fact permits to detect voice activity under high noise, where simple entropy
method fails
A non-linear VAD for noisy environments
This paper deals with non-linear transformations for improving the
performance of an entropy-based voice activity detector (VAD). The idea to use
a non-linear transformation has already been applied in the field of speech
linear prediction, or linear predictive coding (LPC), based on source separation
techniques, where a score function is added to classical equations in order to
take into account the true distribution of the signal. We explore the possibility
of estimating the entropy of frames after calculating its score function, instead
of using original frames. We observe that if the signal is clean, the estimated
entropy is essentially the same; if the signal is noisy, however, the frames
transformed using the score function may give entropy that is different in
voiced frames as compared to nonvoiced ones. Experimental evidence is given
to show that this fact enables voice activity detection under high noise, where
the simple entropy method fails
Evaluation of the neo-glottal closure based on the source description in esophageal voice
The characteristics of esophageal voice render its study by traditional acoustic means to be limited and complicate. These limitations are even stronger when working with patients lacking minimal skills to control the required technique. Nevertheless the speech therapist needs to know the performance and mechanics developed by the patient in producing esophageal voice, as the specific techniques required in this case are not as universal and well-known as the ones for normal voicing. Each patient develops different strategies for producing esophageal voice due to the anatomical changes affecting the crico-pharyngeal sphincter (CPS) and the functional losses resulting from surgery. Therefore it is of fundamental relevance that practitioners could count on new instruments to evaluate esophageal voice quality, which on its turn could help in the enhancement of the CPS dynamics. The present work carries out a description of the voice of four patients after undergoing laryngectomy on data obtained from the study of the neo-glottal wave profile. Results obtained after analyzing the open-close phases and the tension of the muscular body on the CPS are shown
A modulation property of time-frequency derivatives of filtered phase and its application to aperiodicity and fo estimation
We introduce a simple and linear SNR (strictly speaking, periodic to random
power ratio) estimator (0dB to 80dB without additional
calibration/linearization) for providing reliable descriptions of aperiodicity
in speech corpus. The main idea of this method is to estimate the background
random noise level without directly extracting the background noise. The
proposed method is applicable to a wide variety of time windowing functions
with very low sidelobe levels. The estimate combines the frequency derivative
and the time-frequency derivative of the mapping from filter center frequency
to the output instantaneous frequency. This procedure can replace the
periodicity detection and aperiodicity estimation subsystems of recently
introduced open source vocoder, YANG vocoder. Source code of MATLAB
implementation of this method will also be open sourced.Comment: 8 pages 9 figures, Submitted and accepted in Interspeech201
Taking Synchrony Seriously: A Perceptual-Level Model of Infant Synchrony Detection
Synchrony detection between different sensory and/or motor channels appears critically important for young infant learning and cognitive development. For example, empirical studies demonstrate that audio-visual synchrony aids in language acquisition. In this paper we compare these infant studies with a model of synchrony detection based on the Hershey and Movellan (2000) algorithm augmented with methods for quantitative synchrony estimation. Four infant-model comparisons are presented, using audio-visual stimuli of increasing complexity. While infants and the model showed learning or discrimination with each type of stimuli used, the model was most successful with stimuli comprised of one audio and one visual source, and also with two audio sources and a dynamic-face visual motion source. More difficult for the model were stimuli conditions with two motion sources, and more abstract visual dynamicsâan oscilloscope instead of a face. Future research should model the developmental pathway of synchrony detection. Normal audio-visual synchrony detection in infants may be experience-dependent (e.g., Bergeson, et al., 2004)
Mandarin Singing Voice Synthesis Based on Harmonic Plus Noise Model and Singing Expression Analysis
The purpose of this study is to investigate how humans interpret musical
scores expressively, and then design machines that sing like humans. We
consider six factors that have a strong influence on the expression of human
singing. The factors are related to the acoustic, phonetic, and musical
features of a real singing signal. Given real singing voices recorded following
the MIDI scores and lyrics, our analysis module can extract the expression
parameters from the real singing signals semi-automatically. The expression
parameters are used to control the singing voice synthesis (SVS) system for
Mandarin Chinese, which is based on the harmonic plus noise model (HNM). The
results of perceptual experiments show that integrating the expression factors
into the SVS system yields a notable improvement in perceptual naturalness,
clearness, and expressiveness. By one-to-one mapping of the real singing signal
and expression controls to the synthesizer, our SVS system can simulate the
interpretation of a real singer with the timbre of a speaker.Comment: 8 pages, technical repor
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