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NUTS, NARS, and Speech

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Artificial General Intelligence (AGI 2023)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 13921))

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Abstract

To investigate whether “Intelligence is the capacity of an information-processing system to adapt to its environment while operating with insufficient knowledge and resources" [29], we look at utilising the non axiomatic reasoning system (NARS) for speech recognition. This article presents NUTS: raNdom dimensionality redUction non axiomaTic reasoning few Shot learner for perception. NUTS consists of naive dimensionaility reduction, some pre-processing, and then non axiomatic reasoning (NARS). With only 2 training examples NUTS performs similarly to the Whisper Tiny model for discrete word identification.

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Notes

  1. 1.

    For Narsese see https://cis.temple.edu/~pwang/NARS-Intro.html.

  2. 2.

    A grid search showed 4 dimensions was reasonable.

  3. 3.

    Whisper leverages language models greatly improving multiword performance.

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Acknowledgement

We thank reviewers and Parker Lamb for their comments.

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Authors and Affiliations

  1. WiseWorks.AI, London, UK

    Dwane van der Sluis

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  1. Dwane van der Sluis
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Correspondence to Dwane van der Sluis .

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Editors and Affiliations

  1. Department of Psychology, Stockholm University, Stockholm, Sweden

    Patrick Hammer

  2. Örebro University, Örebro, Sweden

    Marjan Alirezaie

  3. University of Gothenburg, Gothenburg, Sweden

    Claes Strannegård

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van der Sluis, D. (2023). NUTS, NARS, and Speech. In: Hammer, P., Alirezaie, M., Strannegård, C. (eds) Artificial General Intelligence. AGI 2023. Lecture Notes in Computer Science(), vol 13921. Springer, Cham. https://doi.org/10.1007/978-3-031-33469-6_31

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  • DOI: https://doi.org/10.1007/978-3-031-33469-6_31

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  • Print ISBN: 978-3-031-33468-9

  • Online ISBN: 978-3-031-33469-6

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