Recently, neural network technology has shown remarkable progress in speech recognition, including word classification, emotion recognition, and identity recognition. This paper introduces three novel speaker recognition methods to improve accuracy. The first method, called long short-term memory with mel-frequency cepstral coefficients for triplet loss (LSTM-MFCC-TL), utilizes MFCC as input features for the LSTM model and incorporates triplet loss and cluster training for effective training. The second method, bidirectional long short-term memory with mel-frequency cepstral coefficients for triplet loss (BLSTM-MFCC-TL), enhances speaker recognition accuracy by employing a bidirectional LSTM model. The third method, bidirectional long short-term memory with mel-frequency cepstral coefficients and autoencoder features for triplet loss (BLSTM-MFCCAE-TL), utilizes an autoencoder to extract additional AE features, which are then concatenated with MFCC and fed into the BLSTM model. The results showed that the performance of the BLSTM model was superior to the LSTM model, and the method of adding AE features achieved the best learning effect. Moreover, the proposed methods exhibit faster computation times compared to the reference GMM-HMM model. Therefore, utilizing pre-trained autoencoders for speaker encoding and obtaining AE features can significantly enhance the learning performance of speaker recognition. Additionally, it also offers faster computation time compared to traditional methods.
This software is complete by Visual C+ + 6.0 and QT, It designed in the Unicode character set patterns , Contribute to ASEAN's cooperation and exchanges, It's solve the problem that system use compatibility and character output garbled in current national language software development. This development model is simple use, stable operation, flexible interface, convenient in user for vocabulary and voice database unified processing (backup, print), at the same time also provides technical guidance to other national language text translation software development. Thai Wen Chinese Translation Electronic dictionary is an important innovation in the field of Dai information technology, providing convenience for "the Belt and Road Initiative" policy. It's the basic support of starting research about minority language cultural information element representation and extraction. And the main function is responsible for Thai queries, translation, reading, etc. Thai WenChinese -English Translation Electronic Dictionary designed to achieve the common functions such as ThaiChinese bilingual translation, Thai people reading and English display. It's also support the thesaurus to add, modify, delete custom actions, it implements the good human-computer interaction function.
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