Rita Singh

Last updated
Rita Singh
Born
India
Alma mater
Known for Artificial intelligence, deep learning, voice analysis, voice forensics
Scientific career
Fields Artificial intelligence, machine learning, cryptography
Institutions Carnegie Mellon University, University of Pittsburgh
Website mlsp.cs.cmu.edu/people/rsingh/index.html

Rita Singh is a computer scientist known for her work in the algorithmic dimensions of voice recognition technologies and the application of artificial intelligence in voice forensics. [1] She holds a position as a Research Faculty in the Language Technologies Institute of the School of Computer Science of Carnegie Mellon University. She led global conversations at the World Economic Forum on topics related to voice technologies. [2] [3] Singh is a founder and technology director of Center for Voice Intelligence and Security (CVIS), an organization dedicated to pioneering developments in voice technology and its security implications. [4]

Contents

Biography

Early Education and Career

Rita Singh completed her early academic pursuits in India, where she received a Bachelor of Science (Hons.) degree in physics and a Master of Science degree in Exploration Geophysics, both from Banaras Hindu University. Her academic journey in geophysics further extended to earning a PhD from the National Geophysical Research Institute of the Council of Scientific and Industrial Research, India, in 1996. [5]

Postdoctoral Fellowship and Initial Research

After completing her PhD, Singh joined the Tata Institute of Fundamental Research in India as a postdoctoral fellow from March 1996 to November 1997. During her fellowship, she was part of the Condensed Matter Physics and Computer Systems and Communications Groups. Her research focused on nonlinear dynamical systems and signal processing, building upon her doctoral work in nonlinear geodynamics and chaos. [5]

Transition to Carnegie Mellon University

In November 1997, Singh transitioned to Carnegie Mellon University (CMU) in Pittsburgh, PA, USA, where she became a member of the research faculty at Language Technologies Institute in the School of Computer Science. At CMU, she affiliated herself with the Robust Speech Recognition and SPHINX Groups. [6] In 2020, she founded Center for Voice Intelligence and Security (CVIS) and currently serves as a technology director.[ citation needed ]

Research

Singh researches primarily in machine learning, deep learning for computer voice recognition, and artificial intelligence applied to voice forensics. [7]

Contributions to Speech Recognition and Audio Processing

Singh's work in computer speech recognition and general audio processing began in 1997. Her research until 2014 encompassed a broad spectrum of topics within this domain. [8] She developed algorithms that contributed to making speech processing systems language-agnostic, automated the discovery and learning of information from speech, and enabled speech processing with minimal reliance on external human-generated knowledge. Her objectives were to enhance automation, devise more effective search strategies, scale up learning algorithms for voice processing systems, and improve their accuracy in complex acoustic environments, including those with high levels of noise. [9]

Human Profiling through Voice Analysis

In December 2014, Singh pioneered the development of the science of profiling humans from their voice. This innovative field involves deducing various human parameters based solely on voice analysis. [10] Singh posits that the human voice, akin to DNA and fingerprints, is unique to each individual and contains an abundance of information about physical, physiological, medical, psychological, sociological, and behavioral aspects, among others. [11] [12] [13] Her approach is grounded in the quantitative analysis of voice signals, leveraging the principles of physics and bio-mechanics of human voice production - leading to an estimation of 3D portrait of a person. [2] [14] A key feature of her methodology is its language-agnostic nature, focusing on the voice signal rather than the semantic or pragmatic content. [15] [16] This language-agnostic nature significantly enhances the application of vocal biomarker technology in medical diagnostics, including the detection of neuromuscular conditions affecting the upper-respiratory tract, as well as diseases such as COVID-19, [17] [18] Alzheimer's, Parkinson's, and coronary artery disease. [19] [20]

Current Endeavors and Future Aspirations

Singh's current research involves designing advanced AI systems to delve into the rich information harbored in the human voice. These systems are being developed for various purposes, including genetic discovery, biomarker identification, and exploring aspects of the human physical state and psyche, such as emotions and personality. Parallel to her work in human profiling, Singh is also engaged in developing core designs for universal speech and audio processing AI systems. Her vision is to create a system capable of replicating the brain's response to multi-sensory inputs. This ambitious project involves not only advanced computing but also integrating aspects of mobility. Singh is actively working on these dimensions to bring her vision to fruition. [1]

Teaching

She teaches the CMU course 11-785 Introduction to Deep Learning and 11-860 Quantum Computing, Cryptography, and Machine Learning Lab.

Previously, she taught:

Books

Singh contributed one chapter to "Techniques for Noise Robustness in Automatic Speech Recognition" (2012) by Wiley. [21] In 2019, she wrote and published "Profiling Humans from their Voice" (2019) by Springer, Singapore [22]

Related Research Articles

Speech recognition is an interdisciplinary subfield of computer science and computational linguistics that develops methodologies and technologies that enable the recognition and translation of spoken language into text by computers. It is also known as automatic speech recognition (ASR), computer speech recognition or speech to text (STT). It incorporates knowledge and research in the computer science, linguistics and computer engineering fields. The reverse process is speech synthesis.

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<span class="mw-page-title-main">Alex Waibel</span> American computer scientist

Alexander Waibel is a professor of Computer Science at Carnegie Mellon University and Karlsruhe Institute of Technology. Waibel's research interests focus on speech recognition and translation and human communication signals and systems. Alex Waibel made pioneering contributions to speech translation systems, breaking down language barriers through cross-lingual speech communication. In fundamental research on machine learning, he is known for the Time Delay Neural Network (TDNN), the first Convolutional Neural Network (CNN) trained by gradient descent, using backpropagation. Alex Waibel introduced the TDNN 1987 at ATR in Japan.

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References

  1. 1 2 "Rita Singh". mlsp.cs.cmu.edu. Retrieved 2024-01-29.
  2. 1 2 Brandon, Simon. "How to catch a criminal using only milliseconds of audio". World Economic Forum.
  3. ↑ "The Mind-Blowing Promise of AI-Driven Voice Profiling". secure.dashdigital.com. Retrieved 2024-02-06.
  4. ↑ "Center for Voice Intelligence and Security". cvis.cs.cmu.edu. Retrieved 2024-01-29.
  5. 1 2 "Rita Singh". IEEE author profile. Retrieved 2024-01-29.
  6. ↑ "CMU Robust Speech Recognition Home Page". www.cs.cmu.edu. Retrieved 2024-01-29.
  7. ↑ "Snapshot: Voice Forensics Can Help the Coast Guard Catch Hoax Callers | Homeland Security". www.dhs.gov. Retrieved 2024-02-06.
  8. ↑ Lambert, Benjamin; Raj, Bhiksha; Singh, Rita (2013-08-25). "Discriminatively trained dependency language modeling for conversational speech recognition". Interspeech 2013. ISCA: ISCA: 3414–3418. doi:10.21437/interspeech.2013-748. S2CID   13538544.
  9. ↑ Raj, Bhiksha; Virtanen, Tuomas; Singh, Rita (2012-10-05). "The Problem of Robustness in Automatic Speech Recognition". Techniques for Noise Robustness in Automatic Speech Recognition: 31–50. doi:10.1002/9781118392683.ch3. ISBN   978-1-119-97088-0.
  10. ↑ Singh, Rita; Raj, Bhiksha; Baker, James (2016). "Short-term analysis for estimating physical parameters of speakers". 2016 4th International Conference on Biometrics and Forensics (IWBF). IEEE. pp. 1–6. doi:10.1109/iwbf.2016.7449696. ISBN   978-1-4673-9448-2. S2CID   9531585.
  11. ↑ "The Mind-Blowing Promise of AI-Driven Voice Profiling". secure.dashdigital.com. Retrieved 2024-02-05.
  12. ↑ Singh, Rita; Keshet, Joseph; Gencaga, Deniz; Raj, Bhiksha (2016). "The relationship of voice onset time and Voice Offset Time to physical age". 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE. pp. 5390–5394. doi:10.1109/icassp.2016.7472707. ISBN   978-1-4799-9988-0. S2CID   8227134.
  13. ↑ Burgess, Matt. "The Race to Hide Your Voice". Wired. ISSN   1059-1028 . Retrieved 2024-02-03.
  14. ↑ "Computer Science Speaker Series Master Calendar". calendars.illinois.edu. Retrieved 2024-02-05.
  15. ↑ Singh, Rita; Raj, Bhiksha; Gencaga, Deniz (2016). "Forensic anthropometry from voice: An articulatory-phonetic approach". 2016 39th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO). IEEE. pp. 1375–1380. doi:10.1109/mipro.2016.7522354. ISBN   978-953-233-086-1. S2CID   15344343.
  16. ↑ "AI in Voice Forensics with Rita Singh". The Women in Tech Show. 2017-11-21. Retrieved 2024-01-29.
  17. ↑ AI and Coronavirus Japan NHK Documentary, NHK, Japan TV Documentary, Aired Saturday, 27 June 2020.
  18. ↑ Tobias, Marc Weber. "AI And Medical Diagnostics: Can A Smartphone App Detect Covid-19 From Speech Or A Cough?". Forbes. Retrieved 2024-02-05.
  19. ↑ Leonard, Ben (2022-01-12). "Talk to me: How AI can diagnose disease". POLITICO. Retrieved 2024-02-05.
  20. ↑ How Voice Profiling Will Revolutionize Health Care, with Rita Singh | News Items Podcast with John Ellis, 2021-08-09, retrieved 2024-02-05
  21. ↑ Virtanen, Tuomas; Singh, Rita; Raj, Bhiksha (2012-11-02), Virtanen, Tuomas; Singh, Rita; Raj, Bhiksha (eds.), "Introduction", Techniques for Noise Robustness in Automatic Speech Recognition (1 ed.), Wiley, pp. 1–5, doi:10.1002/9781118392683.ch1, ISBN   978-1-119-97088-0 , retrieved 2024-02-05
  22. ↑ Singh, Rita (2019). "Profiling Humans from their Voice". Springer. doi:10.1007/978-981-13-8403-5. ISBN   978-981-13-8402-8. S2CID   196188160.
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