Linguistic Knowledge and Empirical Methods in Speech Recognition
نویسنده
چکیده
growing and commercially most promising applications of natural language technology. The technology has achieved a point where carefully designed systems for suitably constrained applications are a reality. Commercial systems are available today for such tasks as large-vocabulary dictation and voice control of medical equipment. This article reviews how state-of-the-art speech-recognition systems combine statistical modeling, linguistic knowledge, and machine learning to achieve their performance and points out some of the research issues in the field.
منابع مشابه
پیشبینی قابلیت فهم همخوانها در افراد دارای شنوایی عادی با استفاده از مدلهای میکروسکوپی دارای معیار فاصله مختلف در بازشناساگر خودکار گفتار
In this study, recognition rates of consonants available in vowel-consonant-vowel structure in hearing tests and two microscopic models will be investigated. Such a syllable structure doesn’t exist in Farsi and Azerbaijani languages, but since the goal is only recognition of middle phoneme, according to hearing tests, listeners are able to properly recognize phonemes in clean speech conditions....
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ورودعنوان ژورنال:
- AI Magazine
دوره 18 شماره
صفحات -
تاریخ انتشار 1997