2. Enhancement of continuous dysarthric speech
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Anusha Prakash
Abstract
Dysarthria is a set of motor-speech disorders resulting due to neurological injuries. It affects the motor component of the motor-speech system. Disruption in muscular control makes the speech imperfect. As a result, dysarthric speech is not as comprehensible as normal speech. Most often, people with dysarthria have problems with communicating and this inhibits their social participation. Hence, for effective communication, it is extremely vital that we develop assistive speech technologies for people with dysarthria. The aim is to improve the naturalness and intelligibility of dysarthric speech while retaining the characteristics of the speaker. For this purpose, durational attributes across dysarthric and normal speech utterances are first studied. An automatic technique is developed to correct dysarthric speech to bring it closer to normal speech. The performance of this technique is compared with that of two other techniques available in the literature - a formant resynthesis technique and a hidden Markov model based adaptive speech synthesis technique. Subjective evaluations show a preference for dysarthric speech modified using the proposed approach over existing approaches.
Abstract
Dysarthria is a set of motor-speech disorders resulting due to neurological injuries. It affects the motor component of the motor-speech system. Disruption in muscular control makes the speech imperfect. As a result, dysarthric speech is not as comprehensible as normal speech. Most often, people with dysarthria have problems with communicating and this inhibits their social participation. Hence, for effective communication, it is extremely vital that we develop assistive speech technologies for people with dysarthria. The aim is to improve the naturalness and intelligibility of dysarthric speech while retaining the characteristics of the speaker. For this purpose, durational attributes across dysarthric and normal speech utterances are first studied. An automatic technique is developed to correct dysarthric speech to bring it closer to normal speech. The performance of this technique is compared with that of two other techniques available in the literature - a formant resynthesis technique and a hidden Markov model based adaptive speech synthesis technique. Subjective evaluations show a preference for dysarthric speech modified using the proposed approach over existing approaches.
Kapitel in diesem Buch
- Frontmatter I
- Foreword V
- Acknowledgments IX
- Contents XI
- List of contributors XIII
- Introduction 1
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Part I: Comparative analysis of methods for speaker identification, speech recognition, and intelligibility modification in the dysarthric speaker population
- 1. State-of-the-art speaker recognition methods applied to speakers with dysarthria 7
- 2. Enhancement of continuous dysarthric speech 35
- 3. Assessment and intelligibility modification for dysarthric speech 67
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Part II: New approaches to speech reconstruction and enhancement via conversion of non-acoustic signals
- 4. Analysis and quality conversion of nonacoustic signals: the physiological microphone (PMIC) 97
- 5. Non-audible murmur to audible speech conversion 125
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Part III: Use of novel speech diagnostic and therapeutic intervention software for speech enhancement and rehabilitation
- 6. Application of speech signal processing for assessment and treatment of voice and speech disorders 153
- 7. A mobile phone-based platform for asynchronous speech therapy 195
Kapitel in diesem Buch
- Frontmatter I
- Foreword V
- Acknowledgments IX
- Contents XI
- List of contributors XIII
- Introduction 1
-
Part I: Comparative analysis of methods for speaker identification, speech recognition, and intelligibility modification in the dysarthric speaker population
- 1. State-of-the-art speaker recognition methods applied to speakers with dysarthria 7
- 2. Enhancement of continuous dysarthric speech 35
- 3. Assessment and intelligibility modification for dysarthric speech 67
-
Part II: New approaches to speech reconstruction and enhancement via conversion of non-acoustic signals
- 4. Analysis and quality conversion of nonacoustic signals: the physiological microphone (PMIC) 97
- 5. Non-audible murmur to audible speech conversion 125
-
Part III: Use of novel speech diagnostic and therapeutic intervention software for speech enhancement and rehabilitation
- 6. Application of speech signal processing for assessment and treatment of voice and speech disorders 153
- 7. A mobile phone-based platform for asynchronous speech therapy 195