Relevant bibliographies by topics / Speech - Signal Processing

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Speech - Signal Processing'

Author: Grafiati
Published: 4 June 2021
Last updated: 6 September 2023

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Consult the lists of relevant articles, books, theses, conference reports, and other scholarly sources on the topic 'Speech - Signal Processing.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Journal articles on the topic "Speech - Signal Processing"

1

Honda, Masaaki, and Takehiro Moriya. "Speech signal processing system." Journal of the Acoustical Society of America 89, no. 1 (January 1991): 491. http://dx.doi.org/10.1121/1.400434.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Yoo, Hah-Young. "Method for processing speech signal in speech processing system." Journal of the Acoustical Society of America 103, no. 4 (April 1998): 1699. http://dx.doi.org/10.1121/1.421327.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Ibragimova, Sayora. "THE ADVANTAGE OFTHEWAVELET TRANSFORM IN PROCESSING OF SPEECH SIGNALS." Technical Sciences 4, no. 3 (March 30, 2021): 37–41. http://dx.doi.org/10.26739/2181-9696-2021-3-6.

Full text
Abstract:
This work deals with basic theory of wavelet transform and multi-scale analysis of speech signals, briefly reviewed the main differences between wavelet transform and Fourier transform in the analysis of speech signals. The possibilities to use the method of wavelet analysis to speech recognition systems and its main advantages. In most existing systems of recognition and analysis of speech sound considered as a stream of vectors whose elements are some frequency response. Therefore, the speech processing in real time using sequential algorithms requires computing resources with high performance. Examples of how this method can be used when processing speech signals and build standards for systems of recognition.Key words: digital signal processing, Fourier transform, wavelet analysis, speech signal, wavelet transform
APA, Harvard, Vancouver, ISO, and other styles
4

Kane, Joi, and Akira Nohara. "Speech signal processing apparatus for extracting a speech signal from a noisy speech signal." Journal of the Acoustical Society of America 96, no. 1 (July 1994): 619. http://dx.doi.org/10.1121/1.410421.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Sawusch, James R. "Seeing Speech: Signal Processing in Speech Research." Contemporary Psychology: A Journal of Reviews 32, no. 3 (March 1987): 280–81. http://dx.doi.org/10.1037/026934.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Schimmel, Claude, and Stan Tempelaars. "Signal Processing, Speech, and Music." Computer Music Journal 21, no. 3 (1997): 101. http://dx.doi.org/10.2307/3681021.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

YEGNANARAYANA, B. "Speech Communication and Signal Processing." Sadhana 36, no. 5 (October 2011): 551–53. http://dx.doi.org/10.1007/s12046-011-0037-1.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

de Abreu, Caio Cesar Enside, Marco Aparecido Queiroz Duarte, Bruno Rodrigues de Oliveira, Jozue Vieira Filho, and Francisco Villarreal. "Regression-Based Noise Modeling for Speech Signal Processing." Fluctuation and Noise Letters 20, no. 03 (January 30, 2021): 2150022. http://dx.doi.org/10.1142/s021947752150022x.

Full text
Abstract:
Speech processing systems are very important in different applications involving speech and voice quality such as automatic speech recognition, forensic phonetics and speech enhancement, among others. In most of them, the acoustic environmental noise is added to the original signal, decreasing the signal-to-noise ratio (SNR) and the speech quality by consequence. Therefore, estimating noise is one of the most important steps in speech processing whether to reduce it before processing or to design robust algorithms. In this paper, a new approach to estimate noise from speech signals is presented and its effectiveness is tested in the speech enhancement context. For this purpose, partial least squares (PLS) regression is used to model the acoustic environment (AE) and a Wiener filter based on a priori SNR estimation is implemented to evaluate the proposed approach. Six noise types are used to create seven acoustically modeled noises. The basic idea is to consider the AE model to identify the noise type and estimate its power to be used in a speech processing system. Speech signals processed using the proposed method and classical noise estimators are evaluated through objective measures. Results show that the proposed method produces better speech quality than state-of-the-art noise estimators, enabling it to be used in real-time applications in the field of robotic, telecommunications and acoustic analysis.
APA, Harvard, Vancouver, ISO, and other styles
9

Mehrzad, M., M. D. Abolhassani, A. H. Jafari, J. Alirezaie, and M. Sangargir. "Cochlear Implant Speech Processing Using Wavelet Transform." ISRN Signal Processing 2012 (August 1, 2012): 1–6. http://dx.doi.org/10.5402/2012/628706.

Full text
Abstract:
We present a method for coding speech signals for the simulation of a cochlear implant. The method is based on a wavelet packet decomposition strategy. We used wavelet packet db4 for 7 levels, generated a series of channels with bandwidths exactly the same as nucleus device, and applied an input stimulus to each channel. The processed signal was then reconstructed and compared to the original signal, which preserved the contents to a high percentage. Finally, performance of the wavelet packet decomposition in terms of computational complexity was compared to other commonly used strategies in cochlear implants. The results showed the power of this method in processing of the input signal for implant users with less complexity than other methods, while maintaining the contents of the input signal to a very good extent.
APA, Harvard, Vancouver, ISO, and other styles
10

Rahman, Md Saifur. "Book Review: Signal Processing of Speech:." International Journal of Electrical Engineering & Education 31, no. 1 (January 1994): 89–90. http://dx.doi.org/10.1177/002072099403100117.

Full text
APA, Harvard, Vancouver, ISO, and other styles
More sources

Dissertations / Theses on the topic "Speech - Signal Processing"

1

Little, M. A. "Biomechanically informed nonlinear speech signal processing." Thesis, University of Oxford, 2007. http://ora.ox.ac.uk/objects/uuid:6f5b84fb-ab0b-42e1-9ac2-5f6acc9c5b80.

Full text
Abstract:
Linear digital signal processing based around linear, time-invariant systems theory finds substantial application in speech processing. The linear acoustic source-filter theory of speech production provides ready biomechanical justification for using linear techniques. Nonetheless, biomechanical studies surveyed in this thesis display significant nonlinearity and non-Gaussinity, casting doubt on the linear model of speech production. In order therefore to test the appropriateness of linear systems assumptions for speech production, surrogate data techniques can be used. This study uncovers systematic flaws in the design and use of exiting surrogate data techniques, and, by making novel improvements, develops a more reliable technique. Collating the largest set of speech signals to-date compatible with this new technique, this study next demonstrates that the linear assumptions are not appropriate for all speech signals. Detailed analysis shows that while vowel production from healthy subjects cannot be explained within the linear assumptions, consonants can. Linear assumptions also fail for most vowel production by pathological subjects with voice disorders. Combining this new empirical evidence with information from biomechanical studies concludes that the most parsimonious model for speech production, explaining all these findings in one unified set of mathematical assumptions, is a stochastic nonlinear, non-Gaussian model, which subsumes both Gaussian linear and deterministic nonlinear models. As a case study, to demonstrate the engineering value of nonlinear signal processing techniques based upon the proposed biomechanically-informed, unified model, the study investigates the biomedical engineering application of disordered voice measurement. A new state space recurrence measure is devised and combined with an existing measure of the fractal scaling properties of stochastic signals. Using a simple pattern classifier these two measures outperform all combinations of linear methods for the detection of voice disorders on a large database of pathological and healthy vowels, making explicit the effectiveness of such biomechanically-informed, nonlinear signal processing techniques.
APA, Harvard, Vancouver, ISO, and other styles
2

Wells, Ian. "Digital signal processing architectures for speech recognition." Thesis, University of the West of England, Bristol, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.294705.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Morris, Robert W. "Enhancement and recognition of whispered speech." Diss., Available online, Georgia Institute of Technology, 2004:, 2003. http://etd.gatech.edu/theses/available/etd-04082004-180338/unrestricted/morris%5frobert%5fw%5f200312%5fphd.pdf.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Coetzee, H. J. "The development of a new objective speech quality measure for speech coding applications." Diss., Georgia Institute of Technology, 1990. http://hdl.handle.net/1853/15474.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Rex, James Alexander. "Microphone signal processing for speech recognition in cars." Thesis, University of Southampton, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.326728.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Shah, Afnan Arafat. "Improving automatic speech recognition transcription through signal processing." Thesis, University of Southampton, 2017. https://eprints.soton.ac.uk/418970/.

Full text
Abstract:
Automatic speech recognition (ASR) in the educational environment could be a solution to address the problem of gaining access to the spoken words of a lecture for many students who find lectures hard to understand, such as those whose mother tongue is not English or who have a hearing impairment. In such an environment, it is difficult for ASR to provide transcripts with Word Error Rates (WER) less than 25% for the wide range of speakers. Reducing the WER reduces the time and therefore cost of correcting errors in the transcripts. To deal with the variation of acoustic features between speakers, ASR systems implement automatic vocal tract normalisation (VTN) that warps the formants (resonant frequencies) of the speaker to better match the formants of the speakers in the training set. The ASR also implements automatic dynamic time warping (DTW) to deal with variation in the speaker’s rate of speaking, by aligning the time series of the new spoken words with the time series of the matching spoken words of the training set. This research investigates whether the ASR’s automatic estimation of VTN and DTW can be enhanced through pre-processing the recording by manually warping the formants and speaking rate of the recordings using sound processing libraries (Rubber Band and SoundTouch) before transcribing the pre-processed recordings using ASR. An initial experiment, performed with the recordings of two male and two female speakers, showed that pre-processing the recording could improve the WER by an average of 39.5% for male speakers and 36.2% for female speakers. However the selection of the best warp factors was achieved through an iterative ‘trial and error’ approach that involved many hours calculating the word error rate for each warp factor setting. Finding a more efficient approach for selecting the warp factors for pre-processing was then investigated. The second experiment investigated the development of a modification function using, as its training set, the best warp factors from the ‘trial and error’ approach to estimate the modification percentage required to improve the WER of a recording. A modification function was found that on average improved the WER by 16% for female speakers and 7% for male speakers.
APA, Harvard, Vancouver, ISO, and other styles
7

Wu, Ping. "Kohonen self-organising neural networks in speech signal processing." Thesis, University of Reading, 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.386985.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Stringer, Paul David. "Binaural signal processing for the enhancement of speech perception." Thesis, University of York, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.282296.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Hanna, Salim Alia. "Digital signal processing algorithms for speech coding and recognition." Thesis, Imperial College London, 1987. http://hdl.handle.net/10044/1/46268.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Toner, Edward. "The enhancement of noise corrupted speech signals." Thesis, University of the West of Scotland, 1993. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.359727.

Full text
APA, Harvard, Vancouver, ISO, and other styles
More sources

Books on the topic "Speech - Signal Processing"

1

Owens, F. J. Signal Processing of Speech. London: Macmillan Education UK, 1993. http://dx.doi.org/10.1007/978-1-349-22599-6.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Owens, Frank J. Signal processing of speech. New York: McGraw-Hill, 1992.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
3

Signal processing of speech. Basingstoke, [England]: Macmillan, 1993.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
4

Kazuo, Nakata, ed. Fundamentals of speech signal processing. New York: Academic Press, 1985.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
5

Saitō, Shūzō. Fundamentals of speech signal processing. New York: Academic Press, 1985.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
6

1945-, Furui Sadaoki, and Sondhi M. Mohan 1933-, eds. Advances in speech signal processing. New York: M. Dekker, 1992.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
7

Gold, Ben, Nelson Morgan, and Dan Ellis. Speech and Audio Signal Processing. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2011. http://dx.doi.org/10.1002/9781118142882.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Signal processing, speech, and music. Lisse [Netherlands]: Swets & Zeitlinger Publishers, 1996.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
9

Society, IEEE Signal Processing. IEEE signal processing letters. New York, NY: IEEE Signal Processing Society, 1994.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
10

Gold, Bernard. Speech and audio signal processing: Processing and perception of speech and music. 2nd ed. Hoboken, N.J: Wiley, 2011.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
More sources

Book chapters on the topic "Speech - Signal Processing"

1

Apte, Shaila Dinkar. "Statistical Speech Processing." In Random Signal Processing, 285–311. Boca Raton : CRC Press, 2018.: CRC Press, 2017. http://dx.doi.org/10.1201/9781315155357-7.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Frerking, Marvin E. "Speech Processing." In Digital Signal Processing in Communication Systems, 490–547. Boston, MA: Springer US, 1994. http://dx.doi.org/10.1007/978-1-4757-4990-8_9.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Sinha, Priyabrata. "Signal Processing Fundamentals." In Speech Processing in Embedded Systems, 9–36. Boston, MA: Springer US, 2009. http://dx.doi.org/10.1007/978-0-387-75581-6_2.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Apte, Shaila Dinkar. "Fundamentals of Speech Processing." In Random Signal Processing, 153–235. Boca Raton : CRC Press, 2018.: CRC Press, 2017. http://dx.doi.org/10.1201/9781315155357-5.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Apte, Shaila Dinkar. "Transform Domain Speech Processing." In Random Signal Processing, 313–63. Boca Raton : CRC Press, 2018.: CRC Press, 2017. http://dx.doi.org/10.1201/9781315155357-8.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Blanchet, Gérard, and Maurice Charbit. "Speech Processing." In Digital Signal and Image Processing Using Matlab®, 105–30. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2015. http://dx.doi.org/10.1002/9781118999592.ch5.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Owens, F. J. "Digital Speech." In Signal Processing of Speech, 17–34. London: Macmillan Education UK, 1993. http://dx.doi.org/10.1007/978-1-349-22599-6_2.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Owens, F. J. "Speech Synthesis." In Signal Processing of Speech, 88–121. London: Macmillan Education UK, 1993. http://dx.doi.org/10.1007/978-1-349-22599-6_5.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Owens, F. J. "Speech Coding." In Signal Processing of Speech, 122–37. London: Macmillan Education UK, 1993. http://dx.doi.org/10.1007/978-1-349-22599-6_6.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Rabiner, Lawrence R. "Speech Recognition Based on Pattern Recognition Approaches." In Signal Processing, 355–68. New York, NY: Springer New York, 1990. http://dx.doi.org/10.1007/978-1-4684-7095-6_19.

Full text
APA, Harvard, Vancouver, ISO, and other styles

Conference papers on the topic "Speech - Signal Processing"

1

"Signal Processing. Speech and Audio Processing." In 2022 29th International Conference on Systems, Signals and Image Processing (IWSSIP). IEEE, 2022. http://dx.doi.org/10.1109/iwssip55020.2022.9854416.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Ali, Syed Imran, Raza Hasan, and M. Sohail Hayat. "Speech and audio processing laboratory: Speech coding related signal processing modules." In 2015 2nd World Symposium on Web Applications and Networking (WSWAN). IEEE, 2015. http://dx.doi.org/10.1109/wswan.2015.7210356.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Leh Luoh, Yu-Zhe Su, and Chih-Fan Hsu. "Speech signal processing based emotion recognition." In 2010 International Conference on System Science and Engineering (ICSSE). IEEE, 2010. http://dx.doi.org/10.1109/icsse.2010.5551812.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

"Track B: Image, signal, speech processing." In 2016 2nd International Conference on Communication, Control & Intelligent Systems (CCIS). IEEE, 2016. http://dx.doi.org/10.1109/ccintels.2016.7878198.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Liu, Fu-Hua, Pedro J. Moreno, Richard M. Stern, and Alejandro Acero. "Signal processing for robust speech recognition." In the workshop. Morristown, NJ, USA: Association for Computational Linguistics, 1994. http://dx.doi.org/10.3115/1075812.1075889.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Lee, Te-Won, Gil-Jin Jang, and Oh-Wook Kwon. "Sparse representation in speech signal processing." In Optical Science and Technology, SPIE's 48th Annual Meeting, edited by Michael A. Unser, Akram Aldroubi, and Andrew F. Laine. SPIE, 2003. http://dx.doi.org/10.1117/12.506153.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Buza, Ovidiu, Gavril Toderean, Alina Nica, and Alexandru Caruntu. "Voice Signal Processing For Speech Synthesis." In 2006 IEEE-TTTC International Conference on Automation, Quality and Testing, Robotics. IEEE, 2006. http://dx.doi.org/10.1109/aqtr.2006.254660.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Skinner, Toby. "Speech signal processing on a neurocomputer." In First International Conference on Spoken Language Processing (ICSLP 1990). ISCA: ISCA, 1990. http://dx.doi.org/10.21437/icslp.1990-67.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Stern, Richard M., Fu-Hua Liu, Pedro J. Moreno, and Alejandro Acero. "Signal processing for robust speech recognition." In 3rd International Conference on Spoken Language Processing (ICSLP 1994). ISCA: ISCA, 1994. http://dx.doi.org/10.21437/icslp.1994-271.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Raghib, Omar, Eshita Sharma, Tameem Ahmad, and Faisal Alam. "Emotion analysis and speech signal processing." In 2017 IEEE International Conference on Power, Control, Signals and Instrumentation Engineering (ICPCSI). IEEE, 2017. http://dx.doi.org/10.1109/icpcsi.2017.8392246.

Full text
APA, Harvard, Vancouver, ISO, and other styles

Reports on the topic "Speech - Signal Processing"

1

Liu, Fu-Hua, Pedro J. Moreno, Richard M. Stern, and Alejandro Acero. Signal Processing for Robust Speech Recognition. Fort Belvoir, VA: Defense Technical Information Center, January 1994. http://dx.doi.org/10.21236/ada457798.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Fan, Howard. High Speed, Numerically Superior Signal Processing Algorithms. Fort Belvoir, VA: Defense Technical Information Center, November 1999. http://dx.doi.org/10.21236/ada370458.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Willson, Jr, and Alan N. VLSI for High-Speed Digital Signal Processing. Fort Belvoir, VA: Defense Technical Information Center, December 1993. http://dx.doi.org/10.21236/ada277617.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Willson, Jr, and Alan N. VLSI for High-Speed Digital Signal Processing. Fort Belvoir, VA: Defense Technical Information Center, September 1994. http://dx.doi.org/10.21236/ada286483.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Willson, Alan N., and Jr. VLSI for High-Speed Digital Signal Processing. Fort Belvoir, VA: Defense Technical Information Center, March 1992. http://dx.doi.org/10.21236/ada250365.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Willson, Jr, and Alan N. VLSI for High-Speed Digital Signal Processing. Fort Belvoir, VA: Defense Technical Information Center, September 1992. http://dx.doi.org/10.21236/ada256654.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Willson, Jr, and Alan N. VLSI for High-Speed Digital Signal Processing. Fort Belvoir, VA: Defense Technical Information Center, December 1992. http://dx.doi.org/10.21236/ada260754.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Willson, Jr, and Alan N. VLSI for High-Speed Digital Signal Processing. Fort Belvoir, VA: Defense Technical Information Center, June 1993. http://dx.doi.org/10.21236/ada267709.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Willson, Jr, and Alan N. VLSI for High-Speed Digital Signal Processing. Fort Belvoir, VA: Defense Technical Information Center, September 1993. http://dx.doi.org/10.21236/ada270406.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Kailath, Thomas. Algorithms and Architectures for High Speed Signal Processing. Fort Belvoir, VA: Defense Technical Information Center, January 1990. http://dx.doi.org/10.21236/ada226203.

Full text
APA, Harvard, Vancouver, ISO, and other styles
You might also be interested in the extended bibliographies on the topic 'Speech - Signal Processing' for particular source types:
Journal articles Dissertations / Theses Books
We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!

To the bibliography