The Recognition of Persian Phonemes Using PPNet
سال انتشار: 1399
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 141
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شناسه ملی سند علمی:
JR_JMSI-10-2_003
تاریخ نمایه سازی: 28 تیر 1402
چکیده مقاله:
Background: In this paper, a novel approach is proposed for the recognition of Persian phonemes in
the Persian consonant‑vowel combination (PCVC) speech dataset. Nowadays, deep neural networks
(NNs) play a crucial role in classification tasks. However, the best results in speech recognition are
not yet as perfect as human recognition rate. Deep learning techniques show outstanding performance
over many other classification tasks, such as image classification and document classification.
Furthermore, the performance is sometimes better than a human. The reason why automatic speech
recognition systems are not as qualified as the human speech recognition system, mostly depends
on features of data which are fed to deep NNs. Methods: In this research, first, the sound samples
are cut for the exact extraction of phoneme sounds in ۵۰ ms samples. Then, phonemes are divided
into ۳۰ groups, containing ۲۳ consonants, ۶ vowels, and a silence phoneme. Results: The short‑time
Fourier transform is conducted on them, and the results are given to PPNet (a new deep convolutional
NN architecture) classifier and a total average of ۷۵.۸۷% accuracy is reached which is the best result
ever compared to other algorithms on separated Persian phonemes (like in PCVC speech dataset).
Conclusion: This method not only can be used for recognizing mono‑phonemes but it can also be
adopted as an input to the selection of the best words in speech transcription
کلیدواژه ها:
نویسندگان
Saber Malekzadeh
Department of Electrical Engineering, Vali‑e‑Asr University of Rafsanjan, Rafsanjan- Khazar University, Baku, Azerbaijan
Mohammad Hossein Gholizadeh
Department of Electrical Engineering, Vali‑e‑Asr University of Rafsanjan, Rafsanjan
Seyed Naser Razavi
Department of Computer Engineering, University of Tabriz, Tabriz, Iran
Hossein Ghayoumi Zadeh
Department of Electrical Engineering, Vali‑e‑Asr University of Rafsanjan, Rafsanjan