Speech Analysis, Synthesis and Perception

By J. Flanagan. 1971

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Dimitrios Ververidis
2. Herman Kamper
3. Constantine Kotropoulos
4. Benjamin van Niekerk
5. Leanne Nortje
6. John H. L. Hansen
7. David F. Harwath
8. James R. Glass

Citations in the corpus

• Nonlinear feature based classification of speech under stress (2001, methodology): “One approach is to model the vocal tract structure using a source-filter model [ 15 ].”
• Text-to-Speech Synthesis (2009, background): “An extensive study into glottal modelling is given in Flanag an [164], which describes various mass/spring/damped systems.”
• The rise and potential of large language model based agents: a survey (2025, unknown): “Furthermore, an audio spectrogram can serve as a medium to endow LLM-based agents with auditory capabilities, as it offers a clear representation of how the frequency spectrum of an audio signal evolves over time [221].”
• Emotional speech recognition: Resources, features, and methods (2006, background): “Keywords: Emotions; Emotional speech data collections; Emotional speech classification; Stress; Interfaces; Acoustic features”
• Vector-quantized neural networks for acoustic unit discovery in the ZeroSpeech 2020 challenge (2020, background): “1As a point of reference, phonetic transcriptions encode speech at a rate of about 50 bits per second [14].”
• Automatic Speech Recognition - A Brief History of the Technology Development (2004, background): “Figure 2 Wheatstone's version of von speaking machine (Flanagan [ 7 ]).”
• Convolutional Neural Network (2020, unknown): “Мел-спектрограмма представляет собой графическое изображение частотного спектра сигнала, изменяющегося во времени, которое широко применяется для анализа речи [8], [9].”