Speech RecognitionIt is a technology that uses computers to recognize human speech. It covers a wide range of areas and is closely related to disciplines such as acoustics, phonetics, linguistics, information theory, pattern recognition theory, and neurobiology.

Mainstream speech recognition technology

• Dynamic Event Warping (DTW): This algorithm uses dynamic warping to combine the time transformation relationship to obtain the distance between feature vectors. It is a classic algorithm in the field of speech recognition.
• Hidden Markov Model HMM: The pronunciation process is represented by the state in the Markov chain. During the word generation process, the system moves from one state to another and generates an output in each state until the word is output.
• Artificial Neural Network ANN: Long training time.

Difficulties in speech recognition

• Recognition performance depends on the surrounding environment. When the training environment is inconsistent with the test environment, the effect will decrease.
• Noise problem, how to effectively reduce noise;
• The ambiguity of phonetic information, such as words with similar pronunciations and words with the same pronunciation but different meanings.

Speech Recognition Application

Speech recognition is becoming a key technology in the field of computer information processing. Its application scope includes voice dialing, voice navigation, indoor equipment control, voice document retrieval, simple dictation data entry, etc. By integrating other natural language processing technologies such as machine translation and speech synthesis, more complex applications can be built, such as translation between voices.