--- title: "Yossi Adi — papers and cards" description: "Yossi Adi: 3 paper cards in the Research library (2024), with what each paper is about, the ideas Mova took from it, and the co-authors." canonical: "https://research.elamur.ai/free/en/authors/yossi-adi/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/yossi-adi/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Yossi Adi # Yossi Adi 3 paper cards in the Research library · 2024 Yossi Adi wrote 3 of the papers Mova reads, in 2024; often with [Amit Roth](https://md.research.elamur.ai/free/en/authors/amit-roth/), [Arnon Turetzky](https://md.research.elamur.ai/free/en/authors/arnon-turetzky/), [Ella Zeldes](https://md.research.elamur.ai/free/en/authors/ella-zeldes/). [OpenAlex](https://openalex.org/A5005191803) · [ORCID](https://orcid.org/0000-0003-2237-3898) · [**h-index 31**](https://openalex.org/authors/A5005191803) · [4543 citations](https://openalex.org/authors/A5005191803) · [160 works](https://openalex.org/works?filter=author.id:A5005191803) — openalex-snapshot, 2026-10-14 The profile is the library's match of the name; two people with one name are not always told apart. Elsewhere: [Google Scholar](https://scholar.google.com/citations?view_op=search_authors&mauthors=Yossi+Adi) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Yossi+Adi) · [dblp](https://dblp.org/search?q=Yossi+Adi) · [ACL Anthology](https://aclanthology.org/search/?q=Yossi+Adi) · [ORCID](https://orcid.org/orcid-search/search?searchQuery=Yossi+Adi) ## Papers 1. **[HebDB: a Weakly Supervised Dataset for Hebrew Speech Processing](https://md.research.elamur.ai/free/en/papers/langstream-2024-turetzky-hebdb-weakly-supervised-dataset-hebrew/)** *(2024)* HebDB is a speech corpus of roughly 2,500 hours of spontaneous Hebrew: podcasts on many topics plus testimonies of World War II survivors, released both raw and pre-processed. 2. **[A Language Modeling Approach to Diacritic-Free Hebrew TTS](https://md.research.elamur.ai/free/en/papers/langstream-2024-roth-language-modeling-approach-diacritic-free/)** *(2024)* The authors build a text-to-speech system for undotted (undiacritized) Hebrew. An autoregressive language model over discrete EnCodec tokens is conditioned on a word-piece encoding of the plain text, with a 3-second acoustic prompt. The model is trained on about 4,500 hours of weakly transcribed podcast speech… 3. **[Enhancing TTS Stability in Hebrew using Discrete Semantic Units](https://md.research.elamur.ai/free/en/papers/langstream-2024-zeldes-enhancing-tts-stability-hebrew-using/)** *(2024)* The paper presents LoTHM, a text-to-speech language model for unvocalised Hebrew. It predicts HuBERT semantic units rather than acoustic codec tokens, so no separate diacritisation step is needed; a vocoder with a speaker embedding then turns the units into audio. The training data is about 4,500 hours of Hebrew… ## Co-authors (11) - [Amit Roth](https://md.research.elamur.ai/free/en/authors/amit-roth/) ×2 - [Arnon Turetzky](https://md.research.elamur.ai/free/en/authors/arnon-turetzky/) ×2 - [Ella Zeldes](https://md.research.elamur.ai/free/en/authors/ella-zeldes/) ×2 - [Or Tal](https://md.research.elamur.ai/free/en/authors/or-tal/) ×2 - Bronya R. Chernyak - Eyal Cohen - Joseph Keshet - Olga Seleznova - Yael Segal-Feldman - Yehoshua Dissen - Yosi Shrem ## More papers in the library (5) Pages of the Research library: our summary, the ideas, references and who cites each. - [Code Llama: Open Foundation Models for Code](https://md.research.elamur.ai/free/en/papers/roziere-2024-code-llama-open-foundation-models/) — Baptiste Rozière, Jonas Gehring, Fabian Gloeckle, et al. · 2024 - [Scaling Speech Technology to 1,000+ Languages](https://md.research.elamur.ai/free/en/papers/pratap-2023-scaling-speech-technology-1-000/) — Vineel Pratap, Andros Tjandra, Bowen Shi, et al. · 2023 - [High Fidelity Neural Audio Compression](https://md.research.elamur.ai/free/en/papers/defossez-2022-high-fidelity-neural-audio-compression/) — Alexandre Defossez, Jade Copet, Gabriel Synnaeve, et al. · 2022 - [On Generative Spoken Language Modeling from Raw Audio](https://md.research.elamur.ai/free/en/papers/lakhotia-2021-generative-spoken-language-modeling-raw/) — Kushal Lakhotia, Eugene Kharitonov, Wei-Ning Hsu, et al. · 2021 - [Fine-grained Analysis of Sentence Embeddings Using Auxiliary Prediction Tasks](https://md.research.elamur.ai/free/en/papers/adi-2016-fine-grained-analysis-sentence-embeddings/) — Yossi Adi, Einat Kermany, Yonatan Belinkov, et al. · 2016