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Baidu Speech Recognition is a technology that converts speech signals into text, which can convert human speech into text data that can be processed by computers. The following is a detailed explanation of the principle, underlying architecture, usage scenarios, code examples and literature materials of C# Baidu speech recognition:
Principle explanation :
Baidu speech recognition is based on deep learning technology, and its principle can be summarized as the following steps:
- Audio collection: The user collects audio signals using devices such as microphones.
- Audio preprocessing: Preprocessing the collected audio signals, including noise reduction, noise removal, etc., to improve the accuracy of subsequent speech recognition.
- Feature extraction: Convert the preprocessed audio into a feature representation. The commonly used feature representation method is to extract features such as the Mel frequency cepstral coefficient (MFCC) of the audio.
- Speech recognition model: The speech recognition model built based on deep learning technology inputs the extracted features and outputs the corresponding text results.
- Post-processing: Post-processing the speech recognition results, including pinyin error correction, grammar correction and other operations to improve recognition accuracy.
- Text output: output the final text result to the user.
Flow chart of the underlying architecture :
The following is a simplified flowchart of the underlying architecture, showing the main process of C# Baidu speech recognition: