Search Results for author: Ahmed Ali

Found 33 papers, 10 papers with code

What do End-to-End Speech Models Learn about Speaker, Language and Channel Information? A Layer-wise and Neuron-level Analysis

no code implementations1 Jul 2021 Shammur Absar Chowdhury, Nadir Durrani, Ahmed Ali

Our results reveal: (i) channel and gender information is omnipresent and is redundantly distributed (ii) complex properties such as dialectal information is encoded only in the task-oriented pretrained network and is localised in the upper layers (iii) a minimal subset of neurons can be extracted to encode the predefined property (iv) salient neurons are sometimes shared between properties and can highlights presence of biases in the network.

Decision Making Dialect Identification +2

KARI: KAnari/QCRI's End-to-End systems for the INTERSPEECH 2021 Indian Languages Code-Switching Challenge

no code implementations10 Jun 2021 Amir Hussein, Shammur Chowdhury, Ahmed Ali

In this paper, we present the Kanari/QCRI (KARI) system and the modeling strategies used to participate in the Interspeech 2021 Code-switching (CS) challenge for low-resource Indian languages.

Fine-tuning Speech Recognition +1

Towards One Model to Rule All: Multilingual Strategy for Dialectal Code-Switching Arabic ASR

no code implementations31 May 2021 Shammur Absar Chowdhury, Amir Hussein, Ahmed Abdelali, Ahmed Ali

We evaluate the system performance handling: (i) monolingual (Ar, En and Fr); (ii) multi-dialectal (Modern Standard Arabic, along with dialectal variation such as Egyptian and Moroccan); (iii) code-switching -- cross-lingual (Ar-En/Fr) and dialectal (MSA-Egyptian dialect) test cases, and compare with current state-of-the-art systems.

automatic-speech-recognition End-To-End Speech Recognition +1

Arabic Speech Recognition by End-to-End, Modular Systems and Human

1 code implementation21 Jan 2021 Amir Hussein, Shinji Watanabe, Ahmed Ali

Recent advances in automatic speech recognition (ASR) have achieved accuracy levels comparable to human transcribers, which led researchers to debate if the machine has reached human performance.

automatic-speech-recognition Speech Recognition

Interpretation of LHCb Hidden-Charm Pentaquarks within the Compact Diquark Model

no code implementations14 Dec 2020 Ahmed Ali, Ishtiaq Ahmed, M. Jamil Aslam, Alexander Parkhomenko, Abdur Rehman

We interpret these narrow resonances as compact hidden-charm diquark-diquark-antiquark pentaquarks.

High Energy Physics - Phenomenology High Energy Physics - Experiment

Tetraquark Interpretation and Production Mechanism of the Belle $Y_b (10750)$-Resonance

no code implementations14 Dec 2020 Ahmed Ali, Luciano Maiani, Alexander Parkhomenko, Wei Wang

Recently, the Belle Collaboration has updated the analysis of the cross sections for the processes $e^+ e^- \to \Upsilon(nS)\, \pi^+ \pi^-$ ($n = 1,\, 2,\, 3$) in the $e^+ e^-$ center-of-mass energy range from 10. 52 to 11. 02~GeV.

High Energy Physics - Phenomenology High Energy Physics - Experiment

Word Error Rate Estimation Without ASR Output: e-WER2

1 code implementation8 Aug 2020 Ahmed Ali, Steve Renals

Measuring the performance of automatic speech recognition (ASR) systems requires manually transcribed data in order to compute the word error rate (WER), which is often time-consuming and expensive.

automatic-speech-recognition Speech Recognition

Predicting the Leading Political Ideology of YouTube Channels Using Acoustic, Textual, and Metadata Information

1 code implementation20 Oct 2019 Yoan Dinkov, Ahmed Ali, Ivan Koychev, Preslav Nakov

Our analysis shows that the use of acoustic signal helped to improve bias detection by more than 6% absolute over using text and metadata only.

Bias Detection Multimodal Deep Learning

DARTS: Dialectal Arabic Transcription System

no code implementations26 Sep 2019 Sameer Khurana, Ahmed Ali, James Glass

We analyze the following; transfer learning from high resource broadcast domain to low-resource dialectal domain and semi-supervised learning where we use in-domain unlabeled audio data collected from YouTube.

Language Modelling Transfer Learning

Analyzing Phonetic and Graphemic Representations in End-to-End Automatic Speech Recognition

1 code implementation9 Jul 2019 Yonatan Belinkov, Ahmed Ali, James Glass

End-to-end neural network systems for automatic speech recognition (ASR) are trained from acoustic features to text transcriptions.

automatic-speech-recognition End-To-End Speech Recognition +2

Domain Attentive Fusion for End-to-end Dialect Identification with Unknown Target Domain

no code implementations4 Dec 2018 Suwon Shon, Ahmed Ali, James Glass

An important issue for end-to-end systems is to have some knowledge of the application domain, because the system can be vulnerable to use cases that were not seen in the training phase; such a scenario is often referred to as a domain mismatched condition.

Dialect Identification

Word Error Rate Estimation for Speech Recognition: e-WER

1 code implementation ACL 2018 Ahmed Ali, Steve Renals

Measuring the performance of automatic speech recognition (ASR) systems requires manually transcribed data in order to compute the word error rate (WER), which is often time-consuming and expensive.

automatic-speech-recognition Language Modelling +4

Convolutional Neural Networks and Language Embeddings for End-to-End Dialect Recognition

2 code implementations12 Mar 2018 Suwon Shon, Ahmed Ali, James Glass

Although the Siamese network with language embeddings did not achieve as good a result as the end-to-end DID system, the two approaches had good synergy when combined together in a fused system.

Sound Audio and Speech Processing

Speech Recognition Challenge in the Wild: Arabic MGB-3

1 code implementation21 Sep 2017 Ahmed Ali, Stephan Vogel, Steve Renals

Two hours of audio per dialect were released for development and a further two hours were used for evaluation.

Dialect Identification Speech Recognition

MIT-QCRI Arabic Dialect Identification System for the 2017 Multi-Genre Broadcast Challenge

no code implementations28 Aug 2017 Suwon Shon, Ahmed Ali, James Glass

In order to achieve a robust ADI system, we explored both Siamese neural network models to learn similarity and dissimilarities among Arabic dialects, as well as i-vector post-processing to adapt domain mismatches.

Dialect Identification Speech Recognition

Findings of the VarDial Evaluation Campaign 2017

no code implementations WS 2017 Marcos Zampieri, Shervin Malmasi, Nikola Ljube{\v{s}}i{\'c}, Preslav Nakov, Ahmed Ali, J{\"o}rg Tiedemann, Yves Scherrer, No{\"e}mi Aepli

We present the results of the VarDial Evaluation Campaign on Natural Language Processing (NLP) for Similar Languages, Varieties and Dialects, which we organized as part of the fourth edition of the VarDial workshop at EACL{'}2017.

Dependency Parsing Dialect Identification

Discriminating between Similar Languages and Arabic Dialect Identification: A Report on the Third DSL Shared Task

no code implementations WS 2016 Shervin Malmasi, Marcos Zampieri, Nikola Ljube{\v{s}}i{\'c}, Preslav Nakov, Ahmed Ali, J{\"o}rg Tiedemann

We present the results of the third edition of the Discriminating between Similar Languages (DSL) shared task, which was organized as part of the VarDial{'}2016 workshop at COLING{'}2016.

Dialect Identification General Classification

Multi-view Dimensionality Reduction for Dialect Identification of Arabic Broadcast Speech

no code implementations19 Sep 2016 Sameer Khurana, Ahmed Ali, Steve Renals

In this work, we present a new Vector Space Model (VSM) of speech utterances for the task of spoken dialect identification.

Dialect Identification Dimensionality Reduction

The MGB-2 Challenge: Arabic Multi-Dialect Broadcast Media Recognition

no code implementations19 Sep 2016 Ahmed Ali, Peter Bell, James Glass, Yacine Messaoui, Hamdy Mubarak, Steve Renals, Yifan Zhang

For language modelling, we made available over 110M words crawled from Aljazeera Arabic website Aljazeera. net for a 10 year duration 2000-2011.

Acoustic Modelling Language Modelling +1

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