1 |
Regular languages extended with reduplication: Formal models, proofs and illustrations
|
|
Wang, Yang. - : eScholarship, University of California, 2021
|
|
BASE
|
|
Show details
|
|
2 |
NOAHQA: Numerical Reasoning with Interpretable Graph Question Answering Dataset ...
|
|
|
|
BASE
|
|
Show details
|
|
3 |
NOAHQA: Numerical Reasoning with Interpretable Graph Question Answering Dataset ...
|
|
|
|
BASE
|
|
Show details
|
|
4 |
Recognizing Reduplicated Forms: Finite-State Buffered Machines ...
|
|
|
|
BASE
|
|
Show details
|
|
5 |
Referring Segmentation in Images and Videos with Cross-Modal Self-Attention Network ...
|
|
|
|
BASE
|
|
Show details
|
|
6 |
A Sequence-to-Sequence Approach to Dialogue State Tracking ...
|
|
|
|
BASE
|
|
Show details
|
|
7 |
Assessment of Use and Fit of Face Masks Among Individuals in Public During the COVID-19 Pandemic in China
|
|
|
|
In: JAMA Netw Open (2021)
|
|
BASE
|
|
Show details
|
|
8 |
Dual Convolutional LSTM Network for Referring Image Segmentation ...
|
|
|
|
BASE
|
|
Show details
|
|
10 |
Cross-Modal Self-Attention Network for Referring Image Segmentation ...
|
|
|
|
BASE
|
|
Show details
|
|
11 |
A critical review of 'English' in China's English education: How far can Chinese teachers embrace ELF?
|
|
|
|
BASE
|
|
Show details
|
|
12 |
DeepDDK: A Deep Learning based Oral-Diadochokinesis Analysis Software
|
|
|
|
In: IEEE EMBS Int Conf Biomed Health Inform (2019)
|
|
BASE
|
|
Show details
|
|
13 |
Translation Analysis of Metaphor Translation in the Black Slaves
|
|
|
|
In: Cross-Cultural Communication; Vol 15, No 4 (2019): Cross-Cultural Communication; 11-14 ; 1923-6700 ; 1712-8358 (2019)
|
|
BASE
|
|
Show details
|
|
14 |
Spelling Error Correction Using a Nested RNN Model and Pseudo Training Data ...
|
|
|
|
BASE
|
|
Show details
|
|
15 |
Relations Between Self-Reported Daily-Life Fatigue, Hearing Status, and Pupil Dilation During a Speech Perception in Noise Task
|
|
|
|
In: Ear Hear (2018)
|
|
BASE
|
|
Show details
|
|
16 |
The Pupil Dilation Response During Speech Perception in Dark and Light: The Involvement of the Parasympathetic Nervous System in Listening Effort
|
|
|
|
BASE
|
|
Show details
|
|
17 |
Immigrants’ Use of eHealth Services in the United States, National Health Interview Survey, 2011-2015
|
|
|
|
BASE
|
|
Show details
|
|
18 |
Relations between self-reported daily-life fatigue, hearing status and pupil dilation during a speech perception in noise task
|
|
|
|
BASE
|
|
Show details
|
|
19 |
Relations between self-reported daily-life fatigue, hearing status, and pupil dilation during a speech perception in noise task
|
|
|
|
BASE
|
|
Show details
|
|
20 |
Application of polyscale methods for speaker verification
|
|
|
|
Abstract:
Voice is a characteristic of the human body which is unique to an individual. Voice can be used for remote access applications, in order to verify the individual’s identity. However, robust feature extraction is required and the aim of this research is the establishment of security via the speaker’s voice. All the experiments in this thesis are based on a dataset recorded in an anechoic chamber, available at the Applied Electromagnetic Laboratory at the University of Manitoba. The following dataset consists of utterances, recorded using 24 volunteers raised in the Province of Manitoba, Canada. To provide a repeatable set of test words that would cover all of the phonemes, the Edinburg Machine Readable Phonetic Alphabet [KiGr08], consisting of 44 words was used. The utterances were recorded using a sampling frequency of 44.1 kilo-samples per second (kSps). The recording sessions took place between 10 AM to 3 PM, from March 27, 2017, until September 27, 2017. This thesis presents a study of text-independent speaker verification with the aim of experimental evaluation of features and embedding fractal algorithms to the front-end processing of the speaker verification system. A voice activity detection based on the variance fractal dimension was used to separate the non-speech segments of the signal. A fusion of multiple features, namely the linear prediction cepstral coefficients, Mel-frequency cepstral coefficients, Higuchi fractal dimension, variance fractal dimension, zero crossing rate, and turns count, was used to form the feature vectors. Meanwhile, an experimental sensitivity analysis was conducted to test the effects of each feature on the accuracy of classification using a support vector machine. The features were extracted using multiple voice activity detection algorithms. The best across-the-divide recognition accuracy of 91.60% was obtained by fusion of all the features that were extracted using the voice activity detection algorithm based on the variance fractal dimension. This shows that fusion of features and embedding of fractal methods to the front-end processing of text-independent speaker verification will increase the accuracy of the classifications. ; October 2018
|
|
Keyword:
Multifractal methods; Polyscale methods; Speaker verification; Voice activity detection
|
|
URL: http://hdl.handle.net/1993/33078
|
|
BASE
|
|
Hide details
|
|
|
|