pith. sign in

arxiv: 2509.02038 · v2 · pith:UHEFKN5Ynew · submitted 2025-09-02 · 💻 cs.CL · cs.SD

NADI 2025: The First Multidialectal Arabic Speech Processing Shared Task

classification 💻 cs.CL cs.SD
keywords subtaskteamsdialectarabicspeechsubmissionsidentificationnadi
0
0 comments X
read the original abstract

We present the findings of the sixth Nuanced Arabic Dialect Identification (NADI 2025) Shared Task, which focused on Arabic speech dialect processing across three subtasks: spoken dialect identification (Subtask 1), speech recognition (Subtask 2), and diacritic restoration for spoken dialects (Subtask 3). A total of 44 teams registered, and during the testing phase, 100 valid submissions were received from eight unique teams. The distribution was as follows: 34 submissions for Subtask 1 "five teams{\ae}, 47 submissions for Subtask 2 "six teams", and 19 submissions for Subtask 3 "two teams". The best-performing systems achieved 79.8% accuracy on Subtask 1, 35.68/12.20 WER/CER (overall average) on Subtask 2, and 55/13 WER/CER on Subtask 3. These results highlight the ongoing challenges of Arabic dialect speech processing, particularly in dialect identification, recognition, and diacritic restoration. We also summarize the methods adopted by participating teams and briefly outline directions for future editions of NADI.

This paper has not been read by Pith yet.

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Forward citations

Cited by 3 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. An End-to-End Hybrid Framework for Rumour Detection in Low-Resources Algerian Dialect

    cs.CL 2026-06 unverdicted novelty 6.0

    Hybrid framework using transformer embeddings plus classical classifier achieves 0.84 F1 for rumour detection in Algerian dialect on a newly constructed dataset from real posts, synthetic data, and FASSILA corpus.

  2. Dziri Voicebot: An End-to-End Low-Resource Speech-to-Speech Conversational System for Algerian Dialect

    cs.CL 2026-06 unverdicted novelty 5.0

    Presents a modular end-to-end speech-to-speech conversational system for Algerian Dialect by fine-tuning pretrained models on dedicated telecom datasets and reports strong component-level performance.

  3. Dziri Voicebot: An End-to-End Low-Resource Speech-to-Speech Conversational System for Algerian Dialect

    cs.CL 2026-06 unverdicted novelty 4.0

    The authors construct and evaluate an end-to-end speech-to-speech pipeline for Algerian Dialect by adapting Whisper for ASR, transformer embeddings for NLU, and a neural TTS on custom dialectal data.