·
DataBubble
  • Home
  • Models
  • News
  • Compare
  • Boards
  • Pricing
  • About
  • Newsletter
  • Methodology
  • Contact
Latest
The US says ASML’s top chip tool may be in China. ASML says it isn’t1h◆Barret Zoph is out at OpenAI again after just five months4h◆Human-AI Agent Interaction in a Business Context5h◆AI4SE and SE4AI Exploration: A Decade Looking Back and Forward5h◆Exit-and-Join Dynamics for Decentralized Coalition Formation5h◆Deontic Policies for Runtime Governance of Agentic AI Systems5h◆Hidden Anchors in Multi-Agent LLM Deliberation5h◆LLM Doesn't Know What It Doesn't Know: Detecting Epistemic Blind Spots via Cross-Model Attribution Divergence on Clinical Tabular Data5h◆Bistable by Construction: Wall-Clock-Calibrated State Monitors Have No Moment-Detection Regime at Agent Cadence5h◆Can In-Context Learning Support Intrinsic Curiosity?5h◆PSCT-Net: Geometry-Aware Pediatric Skull CT Reconstruction via Differentiable Back-Projection and Attention-Guided Refinement5h◆One Probe Won't Catch Them All: Towards Targeted Deception Detection5h◆MoCA-Agent: A Market-of-Claims Code Agent for Financial and Numerical Reasoning5h◆Granularity-Regulated Adaptive Computational Efficiency for Optimal Verification in Test-Time Scaling5h◆When Does Streaming Tool Use Help? Characterizing Tool-Intent Stabilization in Streaming Retrieval-Augmented Generation5h◆ReNikud: Audio-Supervised Hebrew Grapheme-to-Phoneme Conversion5h◆Beyond the GUI Paradigm: Do Mobile Agents Need the Phone Screen?5h◆NEST: Narrative Event Structures in Time for Long Video Understanding5h◆Segment-Level Mandarin Chinese Speech-Based Cognitive Impairment Detection via an Autoencoder with Contrastive Learning5h◆OpenLID-v3: Improving the Precision of Closely Related Language Identification -- An Experience Report5h◆The US says ASML’s top chip tool may be in China. ASML says it isn’t1h◆Barret Zoph is out at OpenAI again after just five months4h◆Human-AI Agent Interaction in a Business Context5h◆AI4SE and SE4AI Exploration: A Decade Looking Back and Forward5h◆Exit-and-Join Dynamics for Decentralized Coalition Formation5h◆Deontic Policies for Runtime Governance of Agentic AI Systems5h◆Hidden Anchors in Multi-Agent LLM Deliberation5h◆LLM Doesn't Know What It Doesn't Know: Detecting Epistemic Blind Spots via Cross-Model Attribution Divergence on Clinical Tabular Data5h◆Bistable by Construction: Wall-Clock-Calibrated State Monitors Have No Moment-Detection Regime at Agent Cadence5h◆Can In-Context Learning Support Intrinsic Curiosity?5h◆PSCT-Net: Geometry-Aware Pediatric Skull CT Reconstruction via Differentiable Back-Projection and Attention-Guided Refinement5h◆One Probe Won't Catch Them All: Towards Targeted Deception Detection5h◆MoCA-Agent: A Market-of-Claims Code Agent for Financial and Numerical Reasoning5h◆Granularity-Regulated Adaptive Computational Efficiency for Optimal Verification in Test-Time Scaling5h◆When Does Streaming Tool Use Help? Characterizing Tool-Intent Stabilization in Streaming Retrieval-Augmented Generation5h◆ReNikud: Audio-Supervised Hebrew Grapheme-to-Phoneme Conversion5h◆Beyond the GUI Paradigm: Do Mobile Agents Need the Phone Screen?5h◆NEST: Narrative Event Structures in Time for Long Video Understanding5h◆Segment-Level Mandarin Chinese Speech-Based Cognitive Impairment Detection via an Autoencoder with Contrastive Learning5h◆OpenLID-v3: Improving the Precision of Closely Related Language Identification -- An Experience Report5h◆
News/A Comparative Study of Pretrained Transformer Models for Quranic ASR: Speech Representations, Label Formats, and Dataset Composition
arxiv
PublishedJune 19, 2026 at 4:00 AM

A Comparative Study of Pretrained Transformer Models for Quranic ASR: Speech Representations, Label Formats, and Dataset Composition

Source
arxiv.orgfull article ↗
Read on arxiv→
Publisher summary· verbatim

arXiv:2606.19747v1 Announce Type: new Abstract: Quran Automatic Speech Recognition (ASR) aims to convert Quranic recitation into text, enabling applications such as aided memorisation tools and Quranic search engines. However, existing ASR models often exhibit high Word Error Rates (WER) on user-rec

Stay posted· Newsletter

A 5-min weekly brief — top movers, price watch, story of the week.

// no spam · unsubscribe one-click · free forever

Discussion
Source
↗
arxiv
Read original ↗All from arxiv →

No replies yet. Be first.

Source
↗
arxiv
Read original ↗All from arxiv →

Related coverage

More from ARXIV
arxivHuman-AI Agent Interaction in a Business Context5harxivAI4SE and SE4AI Exploration: A Decade Looking Back and Forward5harxivExit-and-Join Dynamics for Decentralized Coalition Formation5harxivDeontic Policies for Runtime Governance of Agentic AI Systems5h
The Bubble Brief
WEEKLY

Read AI insights every Tuesday — top movers, new releases, story of the week.

// no spam · unsubscribe one-click · free forever

Originally published on arxiv ↗
HomeModelsNews