สืบค้นงานวิจัย
Two-Stage Gender Identification Using Pitch Frequencies, MFCCs and HMMs
Phoophuangpairoj R. - ไม่ระบุหน่วยงาน
ชื่อเรื่อง (EN): Two-Stage Gender Identification Using Pitch Frequencies, MFCCs and HMMs
ผู้แต่ง / หัวหน้าโครงการ (EN): Phoophuangpairoj R.
บทคัดย่อ (EN): This paper proposes a two-stage method, which can identify the gender of a speaker from spoken syllables that have different tones, using: An average pitch frequency, MFCC-based features (Mel-Frequency Cepstral Coefficients), and Hidden Markov Models (HMM). The method can be divided into 2 stages. At the first stage, an average pitch frequency of each speaker was used to classify the gender. Still, a number of ambiguous speakers who were not clearly classified at the first stage were then forwarded to the second stage. At the second stage, gender identification using: MFCC features, phoneme acoustic models for females and males, and grammar for gender recognition was applied. The experimental results show that the proposed method achieved a high correct gender identification rate of 98.92%, which was higher than the conventional method using an average pitch frequency and a threshold. The proposed method is also more accurate than the Artificial Neural Network (ANN) with pitch frequencies. The results indicate that the proposed method is a practical and efficient way to identify gender. © 2015 IEEE.
บทคัดย่อ: ไม่พบข้อมูลจากหน่วยงานต้นทาง
ภาษา (EN): en
เอกสารแนบ (EN): https://www.scopus.com/inward/record.uri?eid=2-s2.0-84964455442&doi=10.1109%2fSMC.2015.501&partnerID=40&md5=acc4f1bc4687401abda234e3dfed30fd
เผยแพร่โดย (EN): มหาวิทยาลัยมหิดล
คำสำคัญ (EN): Loudspeakers
เจ้าของลิขสิทธิ์ (EN): มหาวิทยาลัยมหิดล
หากไม่พบเอกสารฉบับเต็ม (Full Text) โปรดติดต่อหน่วยงานเจ้าของข้อมูล

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Two-Stage Gender Identification Using Pitch Frequencies, MFCCs and HMMs
Phoophuangpairoj R.
มหาวิทยาลัยมหิดล
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