• Title/Summary/Keyword: natural speech

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Characteristics of the auditory evaluation of good impression using speech manipulation scripts (말소리 변조 스크립트를 이용한 호감도 청취평가 특징)

  • Kwon, Soonbok
    • Phonetics and Speech Sciences
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    • v.8 no.4
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    • pp.131-138
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    • 2016
  • This study analyzes the characteristics of good impression using speech manipulation scripts and investigates the characteristics of preferred speech voice. Fourty male and female college students participated in this study. They have been exposed to the Gyeongsang dialect spoken by their friends and family for more than 15 years. Two sample voices(1 male and 1 female), considered as giving good impression, were subject to voice analysis. Two students were asked to read the sample paragraph of 'Walking' and their voice samples were analyzed through Praat. The collected speech data were manipulated into 4 different sets by changing pitch level, degree of loudness and speech rate. First, both men and women received good impression more from pitch-lowered sound than from the original one. Second, men tended to receive good impression more from slightly louder voice than from the natural-pitched one. Third, it was shown that men often felt more drowned to a voice at slightly faster speech rate than at the original speech rate. Overall, both male and female listeners favored lower pitch over the original pitch. Men tended to prefer louder voice sound while women preferred less loud one. Men received better impression at a lower speech rate but women at a faster speech rate.

Speech Interactive Agent on Car Navigation System Using Embedded ASR/DSR/TTS

  • Lee, Heung-Kyu;Kwon, Oh-Il;Ko, Han-Seok
    • Speech Sciences
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    • v.11 no.2
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    • pp.181-192
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    • 2004
  • This paper presents an efficient speech interactive agent rendering smooth car navigation and Telematics services, by employing embedded automatic speech recognition (ASR), distributed speech recognition (DSR) and text-to-speech (ITS) modules, all while enabling safe driving. A speech interactive agent is essentially a conversational tool providing command and control functions to drivers such' as enabling navigation task, audio/video manipulation, and E-commerce services through natural voice/response interactions between user and interface. While the benefits of automatic speech recognition and speech synthesizer have become well known, involved hardware resources are often limited and internal communication protocols are complex to achieve real time responses. As a result, performance degradation always exists in the embedded H/W system. To implement the speech interactive agent to accommodate the demands of user commands in real time, we propose to optimize the hardware dependent architectural codes for speed-up. In particular, we propose to provide a composite solution through memory reconfiguration and efficient arithmetic operation conversion, as well as invoking an effective out-of-vocabulary rejection algorithm, all made suitable for system operation under limited resources.

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A Study of Speech Control Tags Based on Semantic Information of a Text (텍스트의 의미 정보에 기반을 둔 음성컨트롤 태그에 관한 연구)

  • Chang, Moon-Soo;Chung, Kyeong-Chae;Kang, Sun-Mee
    • Speech Sciences
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    • v.13 no.4
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    • pp.187-200
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    • 2006
  • The speech synthesis technology is widely used and its application area is also being broadened to an automatic response service, a learning system for handicapped person, etc. However, the sound quality of the speech synthesizer has not yet reached to the satisfactory level of users. To make a synthesized speech, the existing synthesizer generates rhythms only by the interval information such as space and comma or by several punctuation marks such as a question mark and an exclamation mark so that it is not easy to generate natural rhythms of people even though it is based on mass speech database. To make up for the problem, there is a way to select rhythms after processing language from a higher level information. This paper proposes a method for generating tags for controling rhythms by analyzing the meaning of sentence with speech situation information. We use the Systemic Functional Grammar (SFG) [4] which analyzes the meaning of sentence with speech situation information considering the sentence prior to the given one, the situation of a conversation, the relationship among people in the conversation, etc. In this study, we generate Semantic Speech Control Tag (SSCT) by the result of SFG's meaning analysis and the voice wave analysis.

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A Model for Post-processing of Speech Recognition Using Syntactic Unit of Morphemes (구문형태소 단위를 이용한 음성 인식의 후처리 모델)

  • 양승원;황이규
    • Journal of Korea Society of Industrial Information Systems
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    • v.7 no.3
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    • pp.74-80
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    • 2002
  • There are many researches on post-processing methods for the Korean continuous speech recognition enhancement using natural language processing techniques. It is very difficult to use a formal morphological analyzer for improving the speech recognition because the analysis technique of natural language processing is mainly for formal written languages. In this paper, we propose a speech recognition enhancement model using syntactic unit of morphemes. This approach uses the functional word level longest match which dose not consider spacing words. We describe the post-processing mechanism for the improving speech recognition by using proposed model which uses the relationship of phonological structure information between predicates md auxiliary predicates or bound nouns that are frequently occurred in Korean sentences.

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The Effect of the Number of Clusters on Speech Recognition with Clustering by ART2/LBG

  • Lee, Chang-Young
    • Phonetics and Speech Sciences
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    • v.1 no.2
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    • pp.3-8
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    • 2009
  • In an effort to improve speech recognition, we investigated the effect of the number of clusters. In usual LBG clustering, the number of codebook clusters is doubled on each bifurcation and hence cannot be chosen arbitrarily in a natural way. To have the number of clusters at our control, we combined adaptive resonance theory (ART2) with LBG and perform the clustering in two stages. The codebook thus formed was used in subsequent processing of fuzzy vector quantization (FVQ) and HMM for speech recognition tests. Compared to conventional LBG, our method was shown to reduce the best recognition error rate by 0${\sim$}0.9% depending on the vocabulary size. The result also showed that between 400 and 800 would be the optimal number of clusters in the limit of small and large vocabulary speech recognitions of isolated words, respectively.

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A Comparison of Effective Feature Vectors for Speech Emotion Recognition (음성신호기반의 감정인식의 특징 벡터 비교)

  • Shin, Bo-Ra;Lee, Soek-Pil
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.67 no.10
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    • pp.1364-1369
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    • 2018
  • Speech emotion recognition, which aims to classify speaker's emotional states through speech signals, is one of the essential tasks for making Human-machine interaction (HMI) more natural and realistic. Voice expressions are one of the main information channels in interpersonal communication. However, existing speech emotion recognition technology has not achieved satisfactory performances, probably because of the lack of effective emotion-related features. This paper provides a survey on various features used for speech emotional recognition and discusses which features or which combinations of the features are valuable and meaningful for the emotional recognition classification. The main aim of this paper is to discuss and compare various approaches used for feature extraction and to propose a basis for extracting useful features in order to improve SER performance.

A Usability Evaluation Method for Speech Recognition Interfaces (음성인식용 인터페이스의 사용편의성 평가 방법론)

  • Han, Seong-Ho;Kim, Beom-Su
    • Journal of the Ergonomics Society of Korea
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    • v.18 no.3
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    • pp.105-125
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    • 1999
  • As speech is the human being's most natural communication medium, using it gives many advantages. Currently, most user interfaces of a computer are using a mouse/keyboard type but the interface using speech recognition is expected to replace them or at least be used as a tool for supporting it. Despite the advantages, the speech recognition interface is not that popular because of technical difficulties such as recognition accuracy and slow response time to name a few. Nevertheless, it is important to optimize the human-computer system performance by improving the usability. This paper presents a set of guidelines for designing speech recognition interfaces and provides a method for evaluating the usability. A total of 113 guidelines are suggested to improve the usability of speech-recognition interfaces. The evaluation method consists of four major procedures: user interface evaluation; function evaluation; vocabulary estimation; and recognition speed/accuracy evaluation. Each procedure is described along with proper techniques for efficient evaluation.

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The Text-to-Speech System Assessment Based on Word Frequency and Word Regularity Effects (단어빈도와 단어규칙성 효과에 기초한 합성음 평가)

  • Nam, Ki-Chun;Choi, Won-Il;Kim, Choong-Myung;Choi, Yang-Gyu;Kim, Jong-Jin
    • MALSORI
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    • no.53
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    • pp.61-74
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    • 2005
  • In the present study, the intelligibility of the synthesized speech sounds was evaluated by using the psycholinguistic and fMRI techniques. In order to see the difference in recognizing words between the natural and synthesized speech sounds, word regularity and word frequency were varied. The results of Experiment1 and Experiment2 showed that the intelligibility difference of the synthesized speech comes from word regularity. In the case of the synthesized speech, the regular words were recognized slower than the irregular words, and there was smaller activation of the auditory areas in brain for the regular words than for the irregular words.

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Syllable-Level Smoothing of Model Parameters for HMM-Based Mixed-Lingual Text-to-Speech (HMM 기반 혼용 언어 음성합성을 위한 모델 파라메터의 음절 경계에서의 평활화 기법)

  • Yang, Jong-Yeol;Kim, Hong-Kook
    • Phonetics and Speech Sciences
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    • v.2 no.1
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    • pp.87-95
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    • 2010
  • In this paper, we address issues associated with mixed-lingual text-to-speech based on context-dependent HMMs, where there are multiple sets of HMMs corresponding to each individual language. In particular, we propose smoothing techniques of synthesis parameters at the boundaries between different languages to obtain more natural quality of speech. In other words, mel-frequency cepstral coefficients (MFCCs) at the language boundaries are smoothed by applying several linear and nonlinear approximation techniques. It is shown from an informal listening test that synthesized speech smoothed by a modified version of linear least square approximation (MLLSA) and a quadratic interpolation (QI) method is preferred than that without using any smoothing technique.

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The Robot Speech Recognition using TMS320VC5510 DSK (TMS320VC5510 DSK를 이용한 음성인식 로봇)

  • Choi, Ji-Hyun;Chung, Ik-Joo
    • Journal of Industrial Technology
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    • v.27 no.A
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    • pp.211-218
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    • 2007
  • As demands for interaction of humans and robots are increasing, robots are expected to be equipped with intelligibility which humans have. Especially, for natural communication, hearing capabilities are so essential that speech recognition technology for robot is getting more important. In this paper, we implement a speech recognizer suitable for robot applications. One of the major problem in robot speech recognition is poor speech quality captured when a speaker talks distant from the microphone a robot is mounted with. To cope with this problem, we used wireless transmission of commands recognized by the speech recognizer implemented using TMS320VC5510 DSK. In addition, as for implementation, since TMS320VC5510 DSP is a fixed-point device, we represent efficient realization of HMM algorithm using fixed-point arithmetic.

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