Phoneme-Based Persian Speech Recognition
This work addresses speech recognition for Persian speakers, but appears incremental as it applies existing techniques to a specific language without clear novelty.
The researchers tackled Persian speech recognition by developing a method using STFT for signal processing and a deep neural network for classification, achieving unspecified results on new sounds.
Undoubtedly, one of the most important issues in computer science is intelligent speech recognition. In these systems, computers try to detect and respond to the speeches they are listening to, like humans. In this research, presenting of a suitable method for the diagnosis of Persian phonemes by AI using the signal processing and classification algorithms have tried. For this purpose, the STFT algorithm has been used to process the audio signals, as well as to detect and classify the signals processed by the deep artificial neural network. At first, educational samples were provided as two phonological phrases in Persian language and then signal processing operations were performed on them. Then the results for the data training have been given to the artificial deep neural network. At the final stage, the experiment was conducted on new sounds.