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Articles 1741 - 1770 of 6273
Full-Text Articles in Entire DC Network
Overview Of The Clef-2023 Checkthat! Lab Task 1 On Check-Worthiness Of Multimodal And Multigenre Content, Firoj Alam, Alberto Barrón-Cedeño, Gullal S. Cheema, Gautam Kishore Shahi, Sherzod Hakimov, Maram Hasanain, Chengkai Li, Rubén Míguez, Hamdy Mubarak, Wajdi Zaghouani, Preslav Nakov
Overview Of The Clef-2023 Checkthat! Lab Task 1 On Check-Worthiness Of Multimodal And Multigenre Content, Firoj Alam, Alberto Barrón-Cedeño, Gullal S. Cheema, Gautam Kishore Shahi, Sherzod Hakimov, Maram Hasanain, Chengkai Li, Rubén Míguez, Hamdy Mubarak, Wajdi Zaghouani, Preslav Nakov
Natural Language Processing Faculty Publications
We present an overview of CheckThat! Lab’s 2023 Task 1, which is part of CLEF-2023. Task 1 asks to determine whether a text item, or a text coupled with an image, is check-worthy. This task places a special emphasis on COVID-19, political debates and transcriptions, and it is conducted in three languages: Arabic, English, and Spanish. A total of 15 teams participated, and most submissions managed to achieve significant improvements over the baselines using Transformer-based models. Out of these, seven teams participated in the multimodal subtask (1A), and 12 teams participated in the Multigenre subtask (1B), collectively submitting 155 official …
Gpachov At Checkthat! 2023: A Diverse Multi-Approach Ensemble For Subjectivity Detection In News Articles, Georgi Pachov, Dimitar Dimitrov, Ivan Koychev, Preslav Nakov
Gpachov At Checkthat! 2023: A Diverse Multi-Approach Ensemble For Subjectivity Detection In News Articles, Georgi Pachov, Dimitar Dimitrov, Ivan Koychev, Preslav Nakov
Natural Language Processing Faculty Publications
The wide-spread use of social networks has given rise to subjective, misleading, and even false information on the Internet. Thus, subjectivity detection can play an important role in ensuring the objectiveness and the quality of a piece of information. This paper presents the solution built by the Gpachov team for the CLEF-2023 CheckThat! lab Task 2 on subjectivity detection. Three different research directions are explored. The first one is based on fine-tuning a sentence embeddings encoder model and dimensionality reduction. The second one explores a sample-efficient few-shot learning model. The third one evaluates fine-tuning a multilingual transformer on an altered …
Enriched Pre-Trained Transformers For Joint Slot Filling And Intent Detection, Momchil Hardalov, Ivan Koychev, Preslav Nakov
Enriched Pre-Trained Transformers For Joint Slot Filling And Intent Detection, Momchil Hardalov, Ivan Koychev, Preslav Nakov
Natural Language Processing Faculty Publications
Detecting the user's intent and finding the corresponding slots among the utterance's words are important tasks in natural language understanding. Their interconnected nature makes their joint modeling a standard part of training such models. Moreover, data scarceness and specialized vocabularies pose additional challenges. Recently, the advances in pre-trained language models, namely contextualized models such as ELMo and BERT have revolutionized the field by tapping the potential of training very large models with just a few steps of fine-tuning on a task-specific dataset. Here, we leverage such models, and we design a novel architecture on top of them. Moreover, we propose …
Grammatical Error Correction: A Survey Of The State Of The Art, Christopher Bryant, Zheng Yuan, Muhammad Reza Qorib, Hannan Cao, Hwee Tou Ng, Ted Briscoe
Grammatical Error Correction: A Survey Of The State Of The Art, Christopher Bryant, Zheng Yuan, Muhammad Reza Qorib, Hannan Cao, Hwee Tou Ng, Ted Briscoe
Natural Language Processing Faculty Publications
Grammatical Error Correction (GEC) is the task of automatically detecting and correcting errors in text. The task not only includes the correction of grammatical errors, such as missing prepositions and mismatched subject–verb agreement, but also orthographic and semantic errors, such as misspellings and word choice errors, respectively. The field has seen significant progress in the last decade, motivated in part by a series of five shared tasks, which drove the development of rule-based methods, statistical classifiers, statistical machine translation, and finally neural machine translation systems, which represent the current dominant state of the art. In this survey paper, we condense …
The Power Of Identity Cues In Text-Based Customer Service: Evidence From Twitter, Yang Gao, Huaxia Rui, Shujing Sun
The Power Of Identity Cues In Text-Based Customer Service: Evidence From Twitter, Yang Gao, Huaxia Rui, Shujing Sun
Research Collection School Of Computing and Information Systems
Text-based customer service is emerging as an important channel through which companies can assist customers. However, the use of few identity cues may cause customers to feel limited social presence and even suspect the human identity of agents, especially in the current age of advanced algorithms. Does such a lack of social presence affect service interactions? We studied this timely question by evaluating the impact of customers’ perceived social presence on service outcomes and customers’ attitudes toward agents. Our identification strategy hinged on Southwest Airlines’ sudden requirement to include a first name in response to service requests on Twitter, which …
Sentence Embedding Approach Using Lstm Auto-Encoder For Discussion Threads Summarization, Abdul Wali Khan, Feras Al-Obeidat, Afsheen Khalid, Adnan Amin, Fernando Moreira
Sentence Embedding Approach Using Lstm Auto-Encoder For Discussion Threads Summarization, Abdul Wali Khan, Feras Al-Obeidat, Afsheen Khalid, Adnan Amin, Fernando Moreira
All Works
Online discussion forums are repositories of valuable information where users interact and articulate their ideas and opinions, and share experiences about numerous topics. These online discussion forums are internet-based online communities where users can ask for help and find the solution to a problem. A new user of online discussion forums becomes exhausted from reading the significant number of irrelevant replies in a discussion. An automated discussion thread summarizing system (DTS) is necessary to create a candid view of the entire discussion of a query. Most of the previous approaches for automated DTS use the continuous bag of words (CBOW) …
Grasp Solution Approach For The E-Waste Collection Problem, Aldy Gunawan, Dang Viet Anh Nguyen, Pham Kien Minh Nguyen, Pieter Vansteenwegen
Grasp Solution Approach For The E-Waste Collection Problem, Aldy Gunawan, Dang Viet Anh Nguyen, Pham Kien Minh Nguyen, Pieter Vansteenwegen
Research Collection School Of Computing and Information Systems
The digital economy has brought significant advancements in electronic devices, increasing convenience and comfort in people’s lives. However, this progress has also led to a shorter life cycle for these devices due to rapid advancements in hardware and software technology. As a result, e-waste collection and recycling have become vital for protecting the environment and people’s health. From the operations research perspective, the e-waste collection problem can be modeled as the Heterogeneous Vehicle Routing Problem with Multiple Time Windows (HVRP-MTW). This study proposes a metaheuristic based on the Greedy Randomized Adaptive Search Procedure complemented by Path Relinking (GRASP-PR) to solve …
Arduinoprog: Towards Automating Arduino Programming, Imam Nur Bani Yusuf, Diyanah Binte Abdul Jamal, Lingxiao Jiang
Arduinoprog: Towards Automating Arduino Programming, Imam Nur Bani Yusuf, Diyanah Binte Abdul Jamal, Lingxiao Jiang
Research Collection School Of Computing and Information Systems
Writing code for Arduino poses unique challenges. A developer 1) needs hardware-specific knowledge about the interface configuration between the Arduino controller and the I/Ohardware, 2) identifies a suitable driver library for the I/O hardware, and 3) follows certain usage patterns of the driver library in order to use them properly. In this work, based on a study of real-world user queries posted in the Arduino forum, we propose ArduinoProg to address such challenges. ArduinoProg consists of three components, i.e., Library Retriever, Configuration Classifier, and Pattern Generator. Given a query, Library Retriever retrieves library names relevant to the I/O hardware identified …
Are We Ready To Embrace Generative Ai For Software Q&A?, Bowen Xu, Thanh-Dat Nguyen, Thanh Le Cong, Thong Hoang, Jiakun Liu, Kisub Kim, Chen Gong, Changan Niu, Chenyu Wang, Xuan-Bach Dinh Le, David Lo
Are We Ready To Embrace Generative Ai For Software Q&A?, Bowen Xu, Thanh-Dat Nguyen, Thanh Le Cong, Thong Hoang, Jiakun Liu, Kisub Kim, Chen Gong, Changan Niu, Chenyu Wang, Xuan-Bach Dinh Le, David Lo
Research Collection School Of Computing and Information Systems
Stack Overflow, the world's largest software Q&A (SQA) website, is facing a significant traffic drop due to the emergence of generative AI techniques. ChatGPT is banned by Stack Overflow after only 6 days from its release. The main reason provided by the official Stack Overflow is that the answers generated by ChatGPT are of low quality. To verify this, we conduct a comparative evaluation of human-written and ChatGPT-generated answers. Our methodology employs both automatic comparison and a manual study. Our results suggest that human-written and ChatGPT-generated answers are semantically similar, however, human-written answers outperform ChatGPT-generated ones consistently across multiple aspects, …
Real: A Representative Error-Driven Approach For Active Learning, Cheng Chen, Yong Wang, Lizi Liao, Yueguo Chen, Xiaoyong Du
Real: A Representative Error-Driven Approach For Active Learning, Cheng Chen, Yong Wang, Lizi Liao, Yueguo Chen, Xiaoyong Du
Research Collection School Of Computing and Information Systems
Given a limited labeling budget, active learning (al) aims to sample the most informative instances from an unlabeled pool to acquire labels for subsequent model training. To achieve this, al typically measures the informativeness of unlabeled instances based on uncertainty and diversity. However, it does not consider erroneous instances with their neighborhood error density, which have great potential to improve the model performance. To address this limitation, we propose Real, a novel approach to select data instances with Representative Errors for Active Learning. It identifies minority predictions as pseudo errors within a cluster and allocates an adaptive sampling budget for …
An Activity System-Based Perspective Of Generative Ai: Challenges And Research Directions, Fiona Fui-Hoon Nah, Jingyuan Cai, Ruilin Zheng, Natalie Pang
An Activity System-Based Perspective Of Generative Ai: Challenges And Research Directions, Fiona Fui-Hoon Nah, Jingyuan Cai, Ruilin Zheng, Natalie Pang
Research Collection School Of Computing and Information Systems
With its remarkable ability to generate content, generative artificial intelligence (GAI) has been recognized as a milestone in the development of artificial general intelligence. To understand the challenges, potential impact, and implications associated with GAI, we adopt a socio-technical perspective to analyze them. First, we identify the key characteristics of GAI, which include content generation, generalization ability, and reinforcement learning based on human feedback. Next, we address technological, ethical, societal, economic, regulatory, and governance challenges. Finally, we deploy activity theory to explore research directions in GAI. Research questions that warrant further investigation include how GAI may impact the future of …
What Is The Best Way To Develop A Website?, Nahomy Julieta Calderon Lopez
What Is The Best Way To Develop A Website?, Nahomy Julieta Calderon Lopez
Theses
This project is centered around empowering individuals with the knowledge and resources necessary for effective website development. The culmination of Thesis/Directed Project II is a user-friendly website designed to distill and present the insights gathered during Thesis/Directed Project I. This website features an engaging interactive quiz, aimed to help the users identify what is the best way, for them, to develop a website. The quiz has multiple questions, each with three distinct response options, the quiz guides users towards one of three key approaches for website development: Website Builders, Content Management System platforms, or Coding. Upon receiving their quiz results, …
The Library & Generative Ai, Nat Gustafson-Sundell, Mark Mccullough
The Library & Generative Ai, Nat Gustafson-Sundell, Mark Mccullough
Library Services Publications
A demonstration of several AI tools, including ChatGPT, ChatPDF, Consensus, and more. The focus of the session is on potential student uses of the tools and related library initiatives, so we address the limits of ChatGPT as an information source. Librarians can help students learn how to use these tools responsibly and provide leadership on campus as AI is integrated into assignments.
Research On Nested Named Entity Recognition In Missile Field Text, Jingwen Guan, Xiao Song, Xiaoqing Li, Tong Yang, Junhua Zhou
Research On Nested Named Entity Recognition In Missile Field Text, Jingwen Guan, Xiao Song, Xiaoqing Li, Tong Yang, Junhua Zhou
Journal of System Simulation
Abstract: Compared with the text recognition in conventional fields, it is difficult to recognize the large number of nested named entities in professional terms. This is also one of the care challenges in building the knowledge graph in aerospace field. For the named entity recognition technologies, bidirectional long short-term memory network plus conditional random field (BiLSTM-CRF) is often used to identify entities, which is difficult to distinguish the complex relationships such as nesting and intersection of terms in missile field. In order to solve the problem, based on the nested entity labeling of domain text, a nested named entity recognition …
One Font Doesn’T Fit All: The Influence Of Digital Text Personalization On Comprehension In Child And Adolescent Readers, Shannon M. Sheppard, Susanne L. Nobles, Anton Palma, Sophie Kajfez, Marjorie Jordan, Kathy Crowley, Sofie Beier
One Font Doesn’T Fit All: The Influence Of Digital Text Personalization On Comprehension In Child And Adolescent Readers, Shannon M. Sheppard, Susanne L. Nobles, Anton Palma, Sophie Kajfez, Marjorie Jordan, Kathy Crowley, Sofie Beier
Communication Sciences and Disorders Faculty Articles and Research
Reading comprehension is an essential skill. It is unclear whether and to what degree typography and font personalization may impact reading comprehension in younger readers. With advancements in technology, it is now feasible to personalize digital reading formats in general technology tools, but this feature is not yet available for many educational tools. The current study aimed to investigate the effect of character width and inter-letter spacing on reading speed and comprehension. We enrolled 94 children (kindergarten–8th grade) and compared performance with six font variations on a word-level semantic decision task (Experiment 1) and a passage-level comprehension task (Experiment 2). …
Dynamic Graph Enhanced Contrastive Learning For Chest X-Ray Report Generation, Mingjie Li, Bingqian Lin, Zicong Chen, Haokun Lin, Xiaodan Liang, Xiaojun Chang
Dynamic Graph Enhanced Contrastive Learning For Chest X-Ray Report Generation, Mingjie Li, Bingqian Lin, Zicong Chen, Haokun Lin, Xiaodan Liang, Xiaojun Chang
Computer Vision Faculty Publications
Automatic radiology reporting has great clinical potential to relieve radiologists from heavy workloads and improve diagnosis interpretation. Recently, researchers have enhanced data-driven neural networks with medical knowledge graphs to eliminate the severe visual and textual bias in this task. The structures of such graphs are exploited by using the clinical dependencies formed by the disease topic tags via general knowledge and usually do not update during the training process. Consequently, the fixed graphs can not guarantee the most appropriate scope of knowledge and limit the effectiveness. To address the limitation, we propose a knowledge graph with Dynamic structure and nodes …
Ifseg: Image-Free Semantic Segmentation Via Vision-Language Model, Sukmin Yun, Seong Hyeon Park, Paul Hongsuck Seo, Jinwoo Shin
Ifseg: Image-Free Semantic Segmentation Via Vision-Language Model, Sukmin Yun, Seong Hyeon Park, Paul Hongsuck Seo, Jinwoo Shin
Machine Learning Faculty Publications
Vision-language (VL) pre-training has recently gained much attention for its transferability and flexibility in novel concepts (e.g., cross-modality transfer) across various visual tasks. However, VL-driven segmentation has been under-explored, and the existing approaches still have the burden of acquiring additional training images or even segmentation annotations to adapt a VL model to downstream segmentation tasks. In this paper, we introduce a novel image-free segmentation task where the goal is to perform semantic segmentation given only a set of the target semantic categories, but without any task-specific images and annotations. To tackle this challenging task, our proposed method, coined IFSeg, generates …
How I Read An Article That Uses Machine Learning Methods, Aziz Nazha, Olivier Elemento, Shannon Mcweeney, Moses Miles, Torsten Haferlach
How I Read An Article That Uses Machine Learning Methods, Aziz Nazha, Olivier Elemento, Shannon Mcweeney, Moses Miles, Torsten Haferlach
Kimmel Cancer Center Faculty Papers
No abstract provided.
N-Shot Benchmarking Of Whisper On Diverse Arabic Speech Recognition, Bashar Talafha, Abdul Waheed, Muhammad Abdul-Mageed
N-Shot Benchmarking Of Whisper On Diverse Arabic Speech Recognition, Bashar Talafha, Abdul Waheed, Muhammad Abdul-Mageed
Natural Language Processing Faculty Publications
Whisper, the recently developed multilingual weakly supervised model, is reported to perform well on multiple speech recognition benchmarks in both monolingual and multilingual settings. However, it is not clear how Whisper would fare under diverse conditions even on languages it was evaluated on such as Arabic. In this work, we address this gap by comprehensively evaluating Whisper on several varieties of Arabic speech for the ASR task. Our evaluation covers most publicly available Arabic speech data and is performed under n-shot (zero-, few-, and full) finetuning. We also investigate the robustness of Whisper under completely novel conditions, such as in …
Research On Multi-Source Heterogeneous Big Data Fusion Based On Wsr, Aihua Li, Weijia Xu, Yong Shi
Research On Multi-Source Heterogeneous Big Data Fusion Based On Wsr, Aihua Li, Weijia Xu, Yong Shi
Bulletin of Chinese Academy of Sciences (Chinese Version)
In the era of multi-source heterogeneous big data, big data presents new features such as cross, diversity and variability. The applications of big data in a wider range of fields have new requirements for data fusion. Under this background, the connotation of data fusion is enriched and expanded. The generalized data fusion includes the fusion of data resources, the fusion of model methods, and the fusion of decision-makers' knowledge and experience. This study analyzes the characteristics of multi-source heterogeneous data fusion at three different fusion levels: data level, information level and decision level, and discusses challenges for data fusion in …
Detecting Team Conflict From Multiparty Dialogue, Ayesha Enayet
Detecting Team Conflict From Multiparty Dialogue, Ayesha Enayet
Electronic Theses and Dissertations, 2020-2023
The emergence of online collaboration platforms has dramatically changed the dynamics of human teamwork, creating a veritable army of virtual teams composed of workers in different physical locations. The global world requires a tremendous amount of collaborative problem solving, primarily virtual, making it an excellent domain for computer scientists and team cognition researchers who seek to understand the dynamics involved in collaborative tasks to provide a solution that can support effective collaboration. Mining and analyzing data from collaborative dialogues can yield insights into virtual teams' thought processes and help develop virtual agents to support collaboration. Good communication is indubitably the …
Studying Memes During Covid Lockdown As A Lens Through Which To Understand Video-Mediated Communication Interactions, Tatyana Claytor
Studying Memes During Covid Lockdown As A Lens Through Which To Understand Video-Mediated Communication Interactions, Tatyana Claytor
Electronic Theses and Dissertations, 2020-2023
The purpose of this study is to analyze image macros about video-mediated communication (VMC) created during the time frame of 2020-2021 when people all over the world started using Zoom and VMC for work and school. It is a unique opportunity to study how users' interactions with themselves and with others were affected at a time when a lot of people started using the technology at the same time. Because the focus is on interactions, I narrowed it down to three topics to analyze the memes: presence, self, and space and place to analyze the memes. I chose memes relating …
Ocr Post-Processing Using Large Language Models, Mahdi Hajiali
Ocr Post-Processing Using Large Language Models, Mahdi Hajiali
UNLV Theses, Dissertations, Professional Papers, and Capstones
Optical Character Recognition (OCR) technology transforms textual visuals into an electronically readable, non-graphical format of the text. This allows the editing and other text manipulation of the content by language technology software such as machine translation, text comprehension, query-answering systems, and search engines. While Optical Character Recognition (OCR) systems continually progress towards greater precision, several complications persist when dealing with low-resolution source images or those with multicolored backgrounds. Consequently, the text derived from OCR necessitates additional refinement to optimize accuracy, beneficial for various subsequent applications. It is recognized that the character accuracy of OCR-generated text may influence certain natural language …
Semantically Structured Creative Computer Systems & Automated Evaluation Of Creative Artifacts, Brad Spendlove
Semantically Structured Creative Computer Systems & Automated Evaluation Of Creative Artifacts, Brad Spendlove
Theses and Dissertations
Computational creativity seeks, in part, to develop autonomous agents that exhibit creativity. Language is an ideal creative domain for studying computer agents due to its rich interconnectedness and immense space of possible combinations. This dissertation explores the design, testing, and theory of creative computer systems that write microfiction and play the board game Codenames. The designs of these systems are all similarly based on building up creative artifacts from the underlying structure of the relationships between words. A critical component of the creative process is the ability to evaluate the quality of creative output. Human and automated assessment of our …
The Student Becomes The Teacher: Training High-Performance Language Models More Sample-Efficiently From Small Models Via Superstilling, Chaz Allen Gundry
The Student Becomes The Teacher: Training High-Performance Language Models More Sample-Efficiently From Small Models Via Superstilling, Chaz Allen Gundry
Theses and Dissertations
Recent advances including the Transformer architecture have revolutionized the Natural Language Processing community by providing immense performance improvements across many tasks, including the development of Large Language Models (LLMs). LLMs show enormous promise as few-shot learners, common-sense knowledge repositories, conversational agents, writing assistants, and coding tools, and are gaining widespread traction in commercial industry. However, LLMs are expensive and time-consuming to train, requiring many passes over terabytes of data for the largest models. In this paper, we present Superstilling, a method for reducing the sample complexity of language model training by distilling the knowledge from a previously-trained model (the teacher) …
Towards Ethical Ai: Mathematics Influences Human Behavior, Dioneia M. Monte-Serrat, Carlo Cattani
Towards Ethical Ai: Mathematics Influences Human Behavior, Dioneia M. Monte-Serrat, Carlo Cattani
Journal of Humanistic Mathematics
Mathematics plays an important role in the linguistic structure of artificial in- telligence (AI). We describe the linguistic process as a unique structure present both in human cognition and in cognitive computing. The close relationship with both AI and human cognition is due to this unique structure, which paves the way for AI to interfere with the behavior of those who interact with it. We highlight the role of mathematicians in designing algorithms—the core of the AI linguistic process—and in defining steps and instructions for AI. Because al- gorithms, through AI, interfere with the thought of those who interact with …
“I Got You”: Centering Identities And Humanness In Collaborations Between Mathematics Educators And Mathematicians, Anne M. Marshall, Sarah Sword, Mollie Applegate, Steven Greenstein, Terrance Pendleton, Kamuela E. Yong, Michael Young, Jennifer A. Wolfe, Theodore Chao, Pamela E. Harris
“I Got You”: Centering Identities And Humanness In Collaborations Between Mathematics Educators And Mathematicians, Anne M. Marshall, Sarah Sword, Mollie Applegate, Steven Greenstein, Terrance Pendleton, Kamuela E. Yong, Michael Young, Jennifer A. Wolfe, Theodore Chao, Pamela E. Harris
Journal of Humanistic Mathematics
Existing literature widely reports on the value of collaborations between mathematicians and mathematics educators, and also how complex those collaborations can be. In this paper, we report on four collaborations that sought to address what mathematics is and who gets to do it. Drawing on the literature and from the careful and intentional work of the collaborators, we offer a framework to capture the richness of those collaborations – one that acknowledges the importance of acknowledging and welcoming the extensive personal and professional experience of each person involved in the collaboration – and a look at how collaborations built with …
Ekstasen: Love Poetry By Felix Hausdorff, Kimberly Gladman
Ekstasen: Love Poetry By Felix Hausdorff, Kimberly Gladman
Journal of Humanistic Mathematics
Four poems by the mathematician Felix Hausdorff are presented in English translation, together with their German originals and commentary about Hausdorff’s multidisciplinary achievements.
S2cd: Self-Heuristic Speaker Content Disentanglement For Any-To-Any Voice Conversion, Pengfei Wei, Xiang Yin, Chunfeng Wang, Zhonghao Li, Xinghua Qu, Zhiqiang Xu, Zejun Ma
S2cd: Self-Heuristic Speaker Content Disentanglement For Any-To-Any Voice Conversion, Pengfei Wei, Xiang Yin, Chunfeng Wang, Zhonghao Li, Xinghua Qu, Zhiqiang Xu, Zejun Ma
Machine Learning Faculty Publications
In this paper, we propose a Self-heuristic Speaker Content Disentanglement (S2CD) model for any to any voice conversion without using any external resources, e.g., speaker labels or vectors, linguistic models, and transcriptions. S2CD is built on the disentanglement sequential variational autoencoder (DSVAE), but improves DSVAE structure at the model architecture level from three perspectives. Specifically, we develop different structures for speaker and content encoders based on their underlying static/dynamic property. We further propose a generative graph, modelled by S2CD, so as to make S2CD well mimic the multi-speaker speech generation process. Finally, we propose a self-heuristic way to introduce bias …
Fooctts: Generating Arabic Speech With Acoustic Environment For Football Commentator, Massa Baali, Ahmed Ali
Fooctts: Generating Arabic Speech With Acoustic Environment For Football Commentator, Massa Baali, Ahmed Ali
Machine Learning Faculty Publications
This paper presents FOOCTTS, an automatic pipeline for a football commentator that generates speech with background crowd noise. The application gets the text from the user, applies text pre-processing such as vowelization, followed by the commentator's speech synthesizer. Our pipeline included Arabic automatic speech recognition for data labeling, CTC segmentation, transcription vowelization to match speech, and fine-tuning the TTS. Our system is capable of generating speech with its acoustic environment within limited 15 minutes of football commentator recording. Our prototype is generalizable and can be easily applied to different domains and languages.