Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Mikhaylovskiy, Nikolay"'
Autor:
Mikhaylovskiy, Nikolay
We propose a shared task of human-like long text generation, LTG Challenge, that asks models to output a consistent human-like long text (a Harry Potter generic audience fanfic in English), given a prompt of about 1000 tokens. We suggest a novel stat
Externí odkaz:
http://arxiv.org/abs/2306.02334
Autor:
Mikhaylovskiy, Nikolay, Churilov, Ilya
We show that the laws of autocorrelations decay in texts are closely related to applicability limits of language models. Using distributional semantics we empirically demonstrate that autocorrelations of words in texts decay according to a power law.
Externí odkaz:
http://arxiv.org/abs/2305.06615
Autor:
Mikhaylovskiy, Nikolay
In this short note we explore what is needed for the unsupervised training of graph language models based on link grammars. First, we introduce the ter-mination tags formalism required to build a language model based on a link grammar formalism of Sl
Externí odkaz:
http://arxiv.org/abs/2208.13021
Autor:
Zubchuk, Eduard, Arhipkin, Mikhail, Menshikov, Dmitry, Karaush, Aleksandr, Mikhaylovskiy, Nikolay
We opensource under CC BY 4.0 license Lib-SibGMU - a university library circulation dataset - for a wide research community, and benchmark major algorithms for recommender systems on this dataset. For a recommender architecture that consists of a vec
Externí odkaz:
http://arxiv.org/abs/2208.12356
Kiosks are a popular self-service option in many fast-food restaurants, they save time for the visitors and save labor for the fast-food chains. In this paper, we propose an effective design of a kiosk shopping cart recommender system that combines a
Externí odkaz:
http://arxiv.org/abs/2202.04145
This memo describes NTR/TSU winning submission for Low Resource ASR challenge at Dialog2021 conference, language identification track. Spoken Language Identification (LID) is an important step in a multilingual Automated Speech Recognition (ASR) syst
Externí odkaz:
http://arxiv.org/abs/2106.00052
This memo describes NTR-TSU submission for SIGTYP 2021 Shared Task on predicting language IDs from speech. Spoken Language Identification (LID) is an important step in a multilingual Automated Speech Recognition (ASR) system pipeline. For many low-re
Externí odkaz:
http://arxiv.org/abs/2104.11985
Autor:
Kolobov, Rostislav, Okhapkina, Olga, Omelchishina, Olga, Platunov, Andrey, Bedyakin, Roman, Moshkin, Vyacheslav, Menshikov, Dmitry, Mikhaylovskiy, Nikolay
The performance of automated speech recognition (ASR) systems is well known to differ for varied application domains. At the same time, vendors and research groups typically report ASR quality results either for limited use simplistic domains (audiob
Externí odkaz:
http://arxiv.org/abs/2103.16193
Autor:
Vygon, Roman, Mikhaylovskiy, Nikolay
Publikováno v:
In: Karpov A., Potapova R. (eds) Speech and Computer. SPECOM 2021. Lecture Notes in Computer Science, vol 12997. Springer, Cham
In the past few years, triplet loss-based metric embeddings have become a de-facto standard for several important computer vision problems, most no-tably, person reidentification. On the other hand, in the area of speech recognition the metric embedd
Externí odkaz:
http://arxiv.org/abs/2101.04792
Publikováno v:
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference [Annu Int Conf IEEE Eng Med Biol Soc] 2021 Nov; Vol. 2021, pp. 1384-1387.
