speech recognition system-25




SPEECH RECOGNITION SYSTEM USING SPEECH CODING ON EVM TMS320C541 BOARD
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ELPG Pop ,ines-conf.org ABSTRACT The contribution presents a speech recognition application developed on the EVM C541 board nsing the CCS (Code Composer Studio). The application represents the implementation of the TESPAR (Time Encoding Signal Processing and Recognition)

A FIRST SPEECH RECOGNITION SYSTEM FOR MANDARIN-ENGLISH CODE-SWITCH CONVERSATIONAL SPEECH
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NT Vu, DC Lyu, J Weiner, D Telaar, T Schlippe ,csl.ira.uka.de ABSTRACT This paper presents first steps toward a large vocabulary continuous speech recognition system (LVCSR) for conversational Mandarin-English code-switching (CS) speech. We applied state-of-the-art techniques such as speaker adaptive and

Spectrogram, embedded system and speech recognition
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R Bucko ,mechatronika.polsl.pl 1. Introduction In present time the recognition of spoken speech is highly developed. Communication using verbal speech is the most basic and natural form of information transfer between people. With new communication and information technology it is becoming necessary to

A Matlab Implementation of a Speech Recognition System Using HMM Models
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ABSTRACT In this study, we present a speech recognition interface designed for vocal control. The implementation has been realized under the Matlab environment with scripts in C. The program uses the statistical HMM (Hidden Markov Models) for speech modeling, the K-

Combining Speech Recognition and Created Realities VXInteractiveTM System to Create A Japanese Language Program That Promotes Student-Directed
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T Squires ,created-realities.com ABSTRACT The potential now exists for the creation of an Internet-based Japanese Language program that will provide a more interactive and motivating learning environment than is possible in the traditional classroom or with current on-line and individualized language

A Speech Recognition System for Urdu Language
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This paper investigates use of a machine learnt model for recognition of individually words spoken in Urdu language. Speech samples from many different speakers were utilized for modeling. Original time-domain samples are normalized and pre-processed by applying

HMM Automatic Speech Recognition System of Arabic Alphadigits
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ABSTRACT Automatic recognition of spoken alphabets and digits is one of the difficult tasks in the field of computer speech recognition. Spoken alphadigits (ie, alphabets and digits) recognition process is needed in many applications that take spoken digits and/or

E-learning Finds a Voice: a Study of a Speech-recognition Interface on an E-learning System.
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E-learning has been in use within commercial environments for many years although often under different names such as computer-based training. Since the early 1980s when they first began, the design of these systems has progressed with developments in technology

ASYNCHRONOUS INTEGRATION OF VISUAL INFORMATION IN AN AUTOMATIC SPEECH RECOGNITION SYSTEM
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F Le Mans ,wagstaff.asel.udel.edu ABSTRACT This paper deals with the integration of visual data in automatic speech recognition systems. We rst describe the framework of our research; the development of advanced multi-user multi-modal interfaces. Then we present audiovisual speech

Implementing a Speech Recognition System on a Graphics Processor Unit (GPU) using CUDA
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A Yi ,eecg.toronto.edu A speech recognition system can be classified based on two factors:(1) whether the system is speaker-dependent or speaker-independent, and (2) whether the system works for continuous speech or isolated words. Ideally, it should be able to recognize each spoken

ISOLATED-WORDS SPEECH RECOGNITION SYSTEM USING VQ WITH MFCC
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CN Kayte, VP Pawar ,aygrt.net ABSTRACT Speech recognition is always looked upon as a fascinating field in human computer interaction. It is one of the fundamental steps towards understanding human cognition and their behavior. This research paper aims to develop an isolated-word

Integrating the speech recognition system SPHINX with the STEP system
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ABSTRACT This thesis performs a set of experiments to assess the prospects of speech interfaces to databases. The particular systems integrated in this thesis are the Sphinx-4 speech recognition system, the STEP natural language interface to databases and text to

CONTINUOUS SPEECH RECOGNITION SYSTEM FOR MALAYALAM LANGUAGE USING PLP CEPSTRAL COEFFICIENT
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C Kurian ,researchmanuscripts.com ABSTRACT Development of Malayalam speech recognition system is in its infancy stage; although many works have been done in other Indian languages. In this paper we present the first work on speaker independent Malayalam continuous speech recognizer based on

Body-Conducted Speech Recognition and its Application to Speech Support System
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In recent years, speech recognition systems have been used in a wide variety of environments, including internal automobile systems. Speech recognition plays a major role in a dialoguetype marine engine operation support system currently under investigation.

TC-STAR 2006 Automatic Speech Recognition Evaluation: The UVIGO System
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ABSTRACT This paper describes the ongoing development of the University of Vigo s Automatic Speech Recognition system (UVIGO) for the automatic transcription of Spanish European Parliamentary Plenary sessions and Spanish Parliamentary sessions. The system was

Development of a speech recognition system for Spanish broadcast news
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One of the ASR applications is the generation of transcripts to facilitate searching through multi-media collections containing spoken data. Especially in the broadcast news domain ASR systems have been successfully deployed to index large collections of news. First of all

A LARGE VOCABULARY REAL TIME CONTINUOUS SPEECH RECOGNITION SYSTEM
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JRR Brodersen, A Stoehte, SN Chen, R Yu ,bwrc.eecs.berkeley.edu Machines based on this architecture can run HMM-speech recognition algorithms that update over 5,000 word-models and over 100K grammar transitions every 10 ins. This computation rate wUi allow realization of real-time recognition of 10.000-to 20,000-wond

Markov Modeling in Hindi Speech Recognition System: A Review
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RK Aggarwal ,csijournal.org To handle the various sources of variability like speaker, environmental and linguistic variability, statistical framework is normally used in any state-of-the-art automatic speech recognition (ASR) system. In this procedure, speech features are extracted at the front-end

classification of gender for emotional speech signal



Hierarchical classification of emotional speech
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were classified at a rate up to 67% correct, and the male utterances were classified correctly with a rate ofTheir work also suggests that gender information impacts emotion classification.Gender information is also considered by Dimitrios et al [5], [6] with more emotion classes.

GMM Supervector Based SVM with Spectral Features for Speech Emotion Recognition.
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The results suggest that the gender information should be considered in speech[3] Ververidis, D., Kotropoulos, C., Pitas, I., Automatic Emotional Speech Classification, in Proc.A: anger; F: fear; H: happiness; N: neutral; S: sadness) Classified Emotion (%) Intended Emotion A F

Speech emotion recognition using support vector machine
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The Support Vector Machine (SVM) is used as classifier to classify different emotional states such as anger, happiness, sadness, neutral[2] D. Ververidis, and C. Kotropoulos, Automatic speech classification to five emotional states based on gender information, Proceedings

Emotional space improves emotion recognition.
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classified as high arousal, and sad-bored on the 87% correctly classified as lowspeaker- independent approach, The maximum recognition rate achieved for both classifications is slightly of arousal dimension gives pretty good results for the three level classification problem, ie

Automatic classification of emotion related user states in spontaneous children'sspeech
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more involved in the problem of recognizing emotions automatically and have started to classify emotions with patterntrum, LTAS) as in [Kraj 07] or classified directly on the frame levelcan be used in combination with other turn level features to improve the classification [Vlas 07

Classification on speech emotion recognition-a comparative study
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In this work, we used PNN, MLP and SVM to classify seven emotions.algorithm is amongst the simplest of all machine learning algorithms: an object is classified by athe emotion classification, Table X depicts that in the two hyper-classes the correct classification reaches 97

Emotion-sensitive human-computer interfaces
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models achieved an accuracy of about 60% while humans were able to classify about 70we were able to achieve an accuracy of about 64% correctly classified segments.A classification system based on emotion-specific bigram probabilities achieved an accuracy of about 47 Ulrike Gut investigates how speakers can be classified into native and non-nativephonemes; Jerome Bellegarda's description of his approach on speaker classification which leverages the Development of a Femininity Estimator for Voice Therapy of Gender Identity Disorder

Using neutral speech models for emotional speech analysis.
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ClassifiedThe results show that this approach can achieve accuracies up to 78% in the binary emotional classification task.A challenging question is how to normalize those features to remove inter- subject, inter-gender, and inter-recording differences, preserv- ing inter

Combining acoustic and language information for emotion recognition.
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For acoustic information, we used two pattern classification meth- ods to classify the emotion states200 training data randomly selected from all the data pool in each gender, and Tablenot have clear-cut boundaries, we need to explore and develop the classification methods to

Improving automatic emotion recognition from speech signals.
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the auto-correlation method [7]. Since pitch values dif- fer for each gender and thea classification accuracy of 57.43 % and 27.48 % for 2 and 5-class classification respectively.achieves 62.58 % and 43.71 % recognition rates for 2-class and 5-class classifications respec- tively.

Expressive speech synthesis using a concatenative synthesizer.
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study systematically possible group differences, ANOVA results yielded no significant gender or languageSpanish language [8] where anger and happiness have been classified as segmental of basic emotions may provide synthesis of various intermediate emotional nuances.

Psychological motivated multi-stage emotion classification exploiting voice quality features
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Similarly, all patterns that were classified to low activation in the first stage are classified to one 5.2 Outlook Although all the presented classifications are speaker independent, the results are strongly optimized for theClassification of glottal vibration from acoustic measurements

Combining categorical and primitives-based emotion recognition
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Page 5. classifications.For comparison, the 3D estimates were classified into the four emotion classes, achieving a recognition rate of 83.5%.[2] D. Ververidis and C. Kotropoulos, Automatic speech classification to five emotional states based on gender information, in Proc.

Gender classification in speech recognition using fuzzy logic and neural network.
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The speaker are classified between Male and Female by computing euclidean distance from thea fuzzy ARTMAP network and modified fuzzy ARTMAP network to classify the various19], have discussed a comparative study of gender and age classification algorithms which is

Multimodal approaches for emotion recognition: a survey
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28 classified physiological patterns for a set of eight emotions (including neutral) by applying patternthe extracted facial features and an HMM has been used to classify the estimatedwith the appropriate vocal emotion, the authors applied a single-modal classification method in

The INTERSPEECH 2009 emotion challenge.
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or side tasks learned as gender, etcN. Amir, L. Kessous, and V. Aharonson, Combining Efforts for Improving Au- tomatic Classification of EmotionalGrimm, Kristian Kroschel, and Shrikanth Narayanan, The Vera am Mittag German Audio-Visual Emotional Speech Database, in

The Social Signal Interpretation Framework (SSI) for Real Time Signal Processing and Recognition.
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Finally, a detected action has to be classified into one out of a set ofthe Mel-frequency cepstral coefficients (MFCCs) and therefore makes more features available for classification.of other factors such as record- ing quality, background noise, user groups (gender, age, etc

A taxonomy of applications that utilize emotional awareness
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In order to check the validity of our taxonomy we will classify our example applications accordingly as generic term for the understanding, emotional tutor and can consistently be classified just asTales of Tuning – Prototyping for Auto- matic Classification of Emotional User States

Gender classification in emotional speech
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Each node sums the activation values weighted possibly by proper weights. The input pattern is finally classified to the class associated to the output node whose value is maximum.This is where SVM2 failed to classify at all.Phoneme-less hierarchical accent classification.

Emotional speech synthesis: a review.
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Abstract Attempts to add emotion effects to synthesised speech have existed for more than a decade now. Several prototypes and fully operational systems have been built based on different synthesis techniques, and quite a number of smaller studies have been

Emotional speech synthesis: from speech database to TTS.
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ABSTRACT Modem Speech synthesisers have achieved a high degree of intelligibility, but can not be regarded as natural-sounding devices. In order to decrease the monotony of synthetic speech, the implementation of emotional effects is now being progressively

Duration and intonation in emotional speech.
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ABSTRACT Three experiments investigated the role of duration and intonation in the expression of emotions in natural and synthetic speech. Two sentences of an actor portraying seven emotions (neutral, joy, boredom, anger, sadness, fear, indignation) were

" You Stupid Tin Box"-Children Interacting with the AIBO Robot: A Cross-linguistic Emotional Speech Corpus.
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Abstract This paper deals with databases that combine different aspects: children's speech, emotional speech, human-robot communication, crosslinguistics, and read vs. spontaneous speech: in a Wizard-of-Oz scenario, German and English children had to instruct Sony's

Analysis and modelling of emotional speech in Spanish
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ICPhS 99 San Francisco Voi 2 Page 959Neutral Happy Sad Cold Anger Surprise il** syllable 135 (+-10.5) i 75 (+-25.2) {+-14.8) 130 (+-19) 217 Í+-32.2) peaks slope 38.8Í+-H.6) 70.9 (+-28.7) 29.6 (+-10.3) 127 (+-19.1)56Í+-32.1) 1* valley 110 {-1-9.6) 112 (+-I6.2) 90

Acoustical analysis of spectral and temporal changes in emotional speech
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ABSTRACT In the present study, the vocal expressions of the emotions anger, happiness, fear, boredom and sadness are acoustically analyzed in relation to neutral speech. The emotional speech material produced by actors is investigated especially with regard to

Validation of an acoustical modelling of emotional expression in Spanish using speechsynthesis techniques
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Ignasi Iriondo, Roger Guaus, Angel Rodríguez, Patricia Lázaro, Norminanda Montoya, Josep Mª Blanco, Dolors Bernadas, Josep Manel Oliver, Daniel Tena and Ludovico LonghiDepartment of Communications and Signal

Real vs. acted emotional speech.
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Abstract Even though the use of actors is a popular method for researching the expression of emotion, little is known about the relation between acted and real emotions. To shed some light on this, we set up a novel experiment, based on the Velten mood induction procedure

An articulatory study of emotional speech production.
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Abstract Few studies exist on the topic of emotion encoding in speech in the articulatory domain. In this report, we analyze articulatory data collected during simulated emotional speech production and investigate differences in speech articulation among four emotion

Generating emotional speech with a concatenative synthesizer.
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ABSTRACT We describe the attempt to synthesize emotional speech With a concatenative speech synthesizer using a parameter space covering not only f0, duration and amplitude, but also voice quality parameters, spectral energy distribution, harmonics-to-noise ratio,

Unit selection and emotional speech.
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Abstract Unit Selection Synthesis, where appropriate units are selected from large databases of natural speech, has greatly improved the quality of speech synthesis. But the quality improvement has come at a cost. The quality of the synthesis relies on the fact that

Design, recording and verification of a danish emotional speech database.
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ABSTRACT A database of recordings of Danish Emotional Speech, DES, has been recorded and analysed. DES has been collected in order to evaluate how well the emotional state in emotional speech is identified by humans. The results sets a standard for

Using neutral speech models for emotional speech analysis.
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Abstract Since emotional speech can be regarded as a variation on neutral (non-emotional) speech, it is expected that a robust neutral speech model can be useful in contrasting different emotions expressed in speech. This study explores this idea by creating acoustic

Study on speaker verification on emotional speech.
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ABSTRACT Besides background noise, channel effect and speaker's health condition, emotion is another factor which may influence the performance of a speaker verification system. In this paper, the performance of a GMM-UBM based speaker verification system

Can automatic speaker verification be improved by training the algorithms on emotional speech
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ABSTRACT The ongoing work described in this contribution attempts to demonstrate the need to train ASV algorithms on emotional speech, in addition to neutral speech, in order to achieve more robust results in real life verification situations. A computerized induction

Constructing emotional speech synthesizers with limited speech database
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Abstract This paper describes an emotional speech synthesis system based on HMMs and related modeling techniques. For concatenative speech synthesis, we require all of the concatenation units that will be used to be recorded beforehand and made available at

The description of naturally occurring emotional speech
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ABSTRACT Most studies of the vocal signs of emotion depend on acted data. This paper reports the development of a vocal coding system to describe the signs of emotion in naturally occurring emotion. The system has been driven by empirical observation, not by

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