arXiv:1609.05104
Intrinsic normalization and extrinsic denormalization of formant data of vowels
원문 초록
Using a known speaker-intrinsic normalization procedure, formant data are scaled by the reciprocal of the geometric mean of the first three formant frequencies. This reduces the influence of the talker but results in a distorted vowel space. The proposed speaker-extrinsic procedure re-scales the normalized values by the mean formant values of vowels. When tested on the formant data of vowels published by Peterson and Barney, the combined approach leads to well separated clusters by reducing the spread due to talkers. The proposed procedure performs better than two top-ranked normalization procedures based on the accuracy of vowel classification as the objective measure.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Using Instruction-Tuned Large Language Models to Identify Indicators of Vulnerability in Police Incident Narratives
Explaining Spectrograms in Machine Learning: A Study on Neural Networks for Speech Classification
Scaling on-chip photonic neural processors using arbitrarily programmable wave propagation
Harmonic-NAS: Hardware-Aware Multimodal Neural Architecture Search on Resource-constrained Devices
STRAPPER: Preference-based Reinforcement Learning via Self-training Augmentation and Peer Regularization
Unlocking the Use of Raw Multispectral Earth Observation Imagery for Onboard Artificial Intelligence
토론
이 논문과 연결된 포럼 글이 아직 없습니다.