Speech recognition methods for speech therapy

Speech therapy focuses on methods for the treatment of speech and language disorders. Speech recognition methods are investigated for computer assisted speech therapy in Turkish. Continuous-mixture hidden Markov models are employed for isolated phoneme and isolated word recognition tasks. Special care is taken for the recognition of confusable words. A Turkish database is designed and collected from native speakers for the evaluations. Initial experiments indicate 84.9% correct recognition rate for isolated phonemes and 94.2% for isolated words when the system is tested in speaker-independent mode. A correct recognition rate of 97.2% is achieved with speaker-dependent training for a list of Turkish words used in speech therapy. The recognition rate between word pairs that contain confusable Turkish phonemes is 88.0%. Speech recognition methods are employed in developing a software tool for speech therapy which can be trained to adapt to the patient´s voice.