Full time PhD position
The UNED IR & NLP group has an open PhD position. The successful candidate is expected to work as part of the joint research project FAIRTRANSNLP-DIAGNOSIS: Measuring and quantifying bias and fairness in NLP pipelines, together with colleagues from the Universidad de Barcelona and Universidad Politécnica de Valencia.
The project focuses on developing methodologies and metrics for measuring bias, fairness and transparency in NLP systems. The detection of bias, their types and sources, is essential for developing unbiased datasets for training fair systems in NLP.
Within the FAIRTRANSNLP project, the PhD candidate will work in the formalization of the detection of bias, fairness, and transparency of NLP pipelines from three different angles: (i) bias embedded in the dataset; (ii) degree of fairness in ML algorithms; and (iii) transparency techniques used in ML to achieve explainability in NLP. The candidate will also participate in the compilation and annotation of datasets.
* Candidate profile *
* Academic background (university degree, preferably master) in computer science or related discipline.
* Knowledge of natural language processing and machine learning.
* Excellent programming skills.
* Ability to research and work as part of a team.
* Fluent in English.
* Terms and conditions *
One year position with a possible extension to three years (1+2) after a positive evaluation. Salary equivalent to a FPI/FPU grant.
* Application *
The position is open until filled. Follow instructions in the official call:
https://www2.uned.es/bici/Curso2022-2023/12212121/11-1.htm#2.-_____
Please send an email to lplaza(a)lsi.uned.es and jcalbornoz(a)lsi.uned.es for more info.
* More about us *
The UNED NLP & IR group is a leading group in Information Retrieval and Natural Language Processing. Our team consists of more than 30 people.
https://sites.google.com/view/nlp-uned/home
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Para más información visite nuestra Política de Privacidad<https://descargas.uned.es/publico/pdf/Politica_privacidad_UNED.pdf>.
[Apologies for cross-posting]
The second workshop on resources and representations for under-resourced language and domains (RESOURCEFUL-2023) explores the role of the kind and the quality of resources that are available to us and challenges and directions for constructing new resources in light of the latest trends in natural language processing.
Data-driven machine-learning techniques in natural language processing have achieved remarkable performance (e.g., BERT, GPT, ChatGPT) but in order to do so large quantities of quality data (which is mostly text) is required. Interpretability studies of large language models in both text-only and multi-modal setups have revealed that even in cases where large text datasets are available, the models still do not cover all the contexts of human social activity and are prone to capturing unwanted bias where data is focused towards only some contexts. A question has also been raised whether textual data is enough to capture semantics of natural language processing and other modalities such as visual representations or a situated context of a robot might be required. Annotator-based resources have been constructed over years based on theoretical work in linguistics, psychology and related fields and a large amount of work has been done both theoretically and practically.
The purpose of the workshop is to initiate a discussion between the two communities involved in building resources (data vs annotation-based) and exploring their synergies for the new challenges in natural language processing. We encourage contributions in the areas of resource creation, representation learning and interpretability in data-driven and expert-driven machine learning setups and both uni-modal and multi-modal scenarios.
In particular we would like to open a forum by bringing together students, researchers, and experts to address and discuss the following questions:
- What is relevant linguistic knowledge the models should capture and how can this knowledge be sampled and extracted in practice?
- What kind of linguistic knowledge do we want and can capture in different contexts and tasks?
- To what degree are resources that have been traditionally aimed at rule-based natural language processing approaches relevant today both for machine learning techniques and hybrid approaches?
- How can they be adapted for data-driven approaches?
- To what degree data-driven approaches can be used to facilitate expert-driven annotation?
- What are current challenges for expert-based annotation?
- How can crowd-sourcing and citizen science be used in building resources?
- How can we evaluate and reduce unwanted biases?
Intended participants are researchers, PhD students and practitioners from diverse backgrounds (linguistics, psychology, computational linguistics, speech, computer science, machine learning, computer vision etc). We foresee an interactive workshop with plenty of time for discussion, complemented with invited talks and presentations of on-going or completed research.
This workshop is a continuation of the first workshop on resources and representations for under-resourced languages and domains held together with the SLTC 2020, https://gu-clasp.github.io/resourceful-2020/.
** Important dates:
- Submission deadline for archival papers: 28th March 2023
- Submission deadline for non-archival papers: 4 April 2023
- Notification of acceptance: 25th April 2023
- Camera-ready version: 9th May 2023
- Workshop date: 22nd May 2023
All deadlines are 11:59PM UTC-12:00 ("anywhere on Earth").
** Submission
We invite submissions of long papers (8 pages), short papers (4 pages), and extended abstracts describing work in progress (2 pages). Submissions can report negative results and be opinion pieces. Both papers and extended abstracts can include any number of pages for references. All submissions must follow the NoDaLida template, available in both LaTeX and MS Word, the templates are available at the official conference website, https://www.nodalida2023.fo/authorkit-nodalida23 Submissions must be anonymous and submitted in the PDF format through OpenReview.
We also invite submissions of non-archival papers related to our theme already presented or published at other venues. These can be submitted in their original formatting. They will be reviewed by the workshop organisers and the accepted ones will be posted on the workshop website.
Authors may be asked to contribute peer-reviews of papers.
** Workshop organisers
Dana Dannélls, Språkbanken Text, University of Gothenburg
Simon Dobnik, CLASP, University of Gothenburg
Adam Ek, CLASP, University of Gothenburg
Stella Frank, University of Copenhagen
Nikolai Ilinykh, CLASP, University of Gothenburg
Beáta Megyesi, Uppsala University
Felix Morger, Språkbanken Text, University of Gothenburg
Joakim Nivre, RISE and Uppsala University
Magnus Sahlgren, AI Sweden
Sara Stymne, Uppsala University
Jörg Tiedemann, University of Helsinki
Lilja Øvrelid, University of Oslo
---
Adam Ek
PhD Student
Centre for Linguistic Theories and Studies in Probability (CLASP)
Department of Philosophy, Linguistics and Theory of Science
University of Gothenburg
adam.ek(a)gu.se
We are inviting applications for a fully funded Ph.D. position in
Multimodal Meeting Summarization at the Cognitive Analytics Research Lab
(CARL) of the Intelligent Systems Research Centre from the School of
Computing, Engineering, and Intelligent Systems, Ulster University. The
project aims to generate automatic minutes of the meeting for multi-party
dialogues using textual, audio, visual, and cognitive modalities.
The position is in collaboration with Dr. Muskaan Singh, Ulster University,
and Prof.Damien Coyle, Director of The Bath Institute for the Augmented
Human (University of Bath) and a UKRI Turing AI Acceleration Fellow
2021-25. *The deadline is due by Monday, 27 February 2023, 4.00 PM UK time.
The interviews are scheduled for 18 April with an expected starting date of
18 September.* he applicants should hold a masters (or be close to
completion) or have equivalent work experience and a publication record.
Solid knowledge of Machine Learning models applied to Natural Language
Processing and Deep Learning is required, as is excellent programming
skills in Python and deep learning frameworks (esp. Keras, TensorFlow or
PyTorch). The scholarship will cover tuition fees at the Home rate and a
maintenance allowance of £18,000 (TBC) per annum for three years (subject
to satisfactory academic performance). This scholarship also comes with
£900 per annum for three years as a research training support grant (RTSG)
allocation to help support the Ph.D. researcher.
For more information and application, please visit,
https://www.ulster.ac.uk/doctoralcollege/find-a-phd/1455768
Please feel free to get in touch with any queries.
*Dr. Muskaan Singh*
Lecturer (~Assistant Professor) in Data Analytics
Cognitive Analytics Research Lab (CARL), Intelligent Systems Research Centre
School of Computing, Engineering and Intelligent Systems
*Room MS138 | Magee Campus | Londonderry | BT48 7JL *
*E:* m.singh(a)ulster.ac.uk *W:*
https://pure.ulster.ac.uk/en/persons/muskaan-singh
Apologies for cross posting
The Third Workshop on Speech and Language Technologies for Dravidian
Languages -(DravidianLangTech-2023)
Link: https://dravidianlangtech.github.io/2023/
The development of technology increases our internet use and most of the
world's languages adapt to it. Whereas the local or under-resourced
languages still pose challenges as they still lack effective technology
developments on their languages, one such language family is the Dravidian
family of languages. Dravidian languages
<https://en.wikipedia.org/wiki/Dravidian_languages> are majorly spoken in
south India and in small pockets in Nepal, Pakistan, Sri Lanka and a few
other places in South Asia. Even though the Proto Dravidian language is
4,500 years old, still the languages of this family are under-resourced in
speech and natural language processing. The Dravidian languages are divided
into four major groups: South, South-Central, Central, and North groups.
Dravidian morphology is agglutinating in that it is exclusively suffixal in
nature. Syntactically, Dravidian languages are head-final and
left-branching. They are free-constituent order languages. To improve
access to and production of information for monolingual speakers of
Dravidian languages, it is necessary to have speech and languages
technologies. The aim of the proposed workshops is especially to prevent
the Dravidian languages from extinction in the context of their use of
technology. This is planned to be the first workshop of this kind on speech
and language technologies for Dravidian languages.
The broader objective of DravidianLangTech-2023 will be
-
To investigate challenges related to speech and language resource
creation for Dravidian languages.
-
To promote research in speech and language technology of Dravidian
languages.
-
To adopt to an appropriate language technology models which suit
Dravidian languages
-
To provide opportunities for researchers from the Dravidian language
community from around the world to collaborate with other researchers.
Call for Papers
DravidianLangTech-2023 welcomes theoretical and practical paper submission
on any Dravidian languages (Tamil, Kannada, Malayalam, Telugu, Tulu,
Allar, Aranadan, Attapadya, Kurumba, Badaga, Beary, Betta Kurumba,
Bharia, Bishavan, Brahui, Chenchu, Duruwa, Eravallan, Gondi,
Holiya, Irula, Jeseri, Kadar, Kaikadi, Kalanadi, Kanikkaran,
Khiwar, Kodava, Kolami, Konda, Koraga, Kota, Koya, Kurambhag
Paharia, Kui, Kumbaran, Kunduvadi, Kurichiya, Kurukh, Kurumba, Kuvi,
Madiya, Mala Malasar, Malankuravan, Malapandaram, Malasar, Malto,
Manda, Muduga, Mullu Kurumba, Muria, Muthuvan, Naiki, Ollari, Paliyan,
Paniya, Pardhan, Pathiya, Pattapu, Pengo, Ravula, Sholaga, Thachanadan,
Toda, Wayanad Chetti, and Yerukala) that contributes to research in
language processing, speech technologies or resources for the same. We will
particularly encourage studies that address either practical application or
improving resources for a given language in the field.
We invite submissions on topics that include, but are not limited to, the
following:
-
Code-mixing/Code-switching
-
Cognitive Modeling and Psycholinguistics
-
Computer-assisted language learning (CALL)
-
Corpus development, tools, analysis and evaluation
-
COVID-19 alert, NLP Applications for Emergency Situations and Crisis
Management
-
Equality, Diversity, and Inclusion
-
Fake News, Spam, and Rumor Detection
-
Hate speech detection and Offensive Language Detection
-
Lexicons and Machine-readable dictionaries
-
Linguistic Theories, Phonology, Morphological analysis, Syntax and
Semantics
-
Machine Translation, Sentiment Analysis, and Text summarization
-
Multimodal Analysis
-
Speech technology and Automatic Speech Recognition
Important dates
-
First call for workshop papers: 15 February 2023
-
Second call for workshop papers: 15 March 2023
-
Workshop paper due: 10 July 2023
-
Notification of acceptance: 5 August 2023
-
Camera-ready papers due: 20 August 2023
-
Workshop dates: 8 September 2023
with regards,
Dr. Bharathi Raja Chakravarthi,
Assistant Professor / Lecturer-above-the-bar
School of Computer Science, University of Galway, Ireland
Insight SFI Research Centre for Data Analytics, Data Science Institute,
University of Galway, Ireland
E-mail: bharathiraja.akr(a)gmail.com , bharathi.raja(a)universityofgalway.ie
<bharathiraja.asokachakravarthi(a)universityofgalway.ie>
Google Scholar: https://scholar.google.com/citations?user=irCl028AAAAJ&hl=en
Special Issue on Language Technology for Safer Online Social Media
Platforms in Low-resource Eurasian Languages
<https://dl.acm.org/pb-assets/static_journal_pages/tallip/pdf/TALLIP-SI-Lang…>
Cyber-Social Issues Prediction in Low-Resource Languages with Deep Internet
of Things (DIoT)
<https://dl.acm.org/pb-assets/static_journal_pages/tallip/pdf/TALLIP-SI-Pred…>
Dear all,
We cordially invite you to take part in the simultaneous speech translation
task <https://iwslt.org/2023/simultaneous> at IWSLT 2023
<https://iwslt.org/2023/>, the 20th edition of the conference!
As with previous years, the task will include a speech-to-text track in
three languages: English to German, English to Japanese, and English to
Chinese. Additionally, we are introducing a new *speech-to-speech track*.
Different from previous years, we will adopt a single latency constraint
for simplified submission.
Here are important dates for the evaluation campaign:
Jan 14, 2023: Release of shared task training and dev data
Apr 1-15, 2023: Evaluation period
Apr 24, 2023: Scientific paper submission deadline
May 22, 2023: Notification of acceptance
June 6, 2023: Camera ready paper due
July 12, 2023: Pre-recorded video due
If you have any queries or comments regarding the task description, please
do not hesitate to reach out to us.
Best Regards,
On behalf of the simultaneous shared task organization team
<https://iwslt.org/2023/simultaneous#organizers>,
Pengwei Li
(Deadline extension)
UCLouvain is looking for:
a postdoctoral researcher in machine learning / natural language processing
- Full-time (100%) fixed-term contract of two years
- for the Centre de traitement automatique du langage (Cental) within the
Institut Langage & Communication (IL&C) in UCLouvain (Louvain-la-Neuve)
- Start date : as soon as possible
This postdoctoral position offer is part of a research project led by the
Cental (https://uclouvain.be/fr/instituts-recherche/ilc/cental) around
legal data processing.
Regarding the concrete application, the project aims at automatizing
the analysis
of documents related to clinic trials (meeting minutes, legal documents,
contracts, ...) to assess their compliance to RGPD. The proposed solution
should thus be flexible enough to, on one hand, ensure that the model(s)
can be adapted to the various document types and, on the other hand, limit
the need of specialists' expertise for training data annotation. In
consequence, the scientific core of this project is directly related fo the
question of few-shot learning, which we intend to address through active
learning and meta-learning.
The role of the hired postdoc will be to (1) develop the resources needed
for learning, (2) implement an architecture that incorporates active
learning and meta-learning, (3) evaluate the models and (4) implement the
components into a web service. The postdoc will also be required to
disseminate the results through scientific publications and/or reports.
Work environment:
CENTAL is part of the Institut Langage & Communication (
https://uclouvain.be/fr/instituts-recherche/ilc), in UCLouvain. This
university is located in Louvain-la-Neuve, Belgium (
https://uclouvain.be/fr/sites/louvain-la-neuve), a walkable city, that offers
a pleasant and dynamic living environment. The research project will be
supervised by Patrick Watrin.
Required skills:
- A completed PhD in Computer Science, Machine Learning, NLP or a similar
domain.
- Excellent programming skills:
- Python
- TensorFlow/Keras or PyTorch
- Linux (server administration)
- Knowledge of the main supervised learning algorithms and deep learning
algorithms is required
- A good knowledge of the main NLP tools and algorithms is a plus
- Strong research track record (publications, conferences, etc.)
- Autonomy, teamwork, ability to understand and analyze needs,
adaptability
- Excellent command of the French language (at least C1) and good command
of English (at least B2)
Conditions:
- Fixed-term contract of one year, renewable once
- Salary based on experience, ranging from 4250€ to 4850€ (monthly, gross)
The position requires residency in Belgium. Candidates from outside the EU
are responsible for obtaining the adequate visa and/or permits, with support
from the UCLouvain.
How to apply:
- Deadline : March 31
- The application file should be sent electronically to Patrick Watrin (
patrick.watrin(a)uclouvain.be) and contain:
- A detailed resume showing the adequate qualifications and skills,
as well and the scientific/academic experiences and publications;
- A cover letter in french, describing your interest for the role,
how your profile complies with the project's needs, etc.;
- A recommendation letter in french or in english.
The shortlisted candidates will be invited to participate in a remote videocall
(details will be communicated in a timely manner).
Call for papers
Workshop Discourse studies and linguistic data science: Addressing challenges in interoperability, multilinguality and linguistic data processing - DiSLiDaS 2023
University of Vienna, Vienna, Austria
12-13 September 2023 (TBA)
Website: http://dislidas.mozajka.co<http://dislidas.mozajka.co/>
The fourth biennial conference on Language, Data and Knowledge (LDK 2023) (http://2023.ldk-conf.org<http://2023.ldk-conf.org/>) and Cost Action CA18209 NexusLinguarum (https://nexuslinguarum.eu<https://nexuslinguarum.eu/>) are glad to announce the second workshop Discourse studies and linguistic data science: Addressing challenges in interoperability, multilinguality and linguistic data processing – DiSLiDaS 2023.
*Conference aims and topics*
The workshop aims to follow through the topics discussed during DiSLiDaS 2022 (https://dislidas.mozajka.co/?page_id=211) and to gather current research advances in discourse analysis and representation, in the context of multilinguality, from a linguistic and computational perspective. We invite submissions addressing challenges such as interoperability, linguistic linked open data (LLOD), and language processing and analysis.
The workshop topics are the following (but not limited to):
● Discourse and dialogue annotation: Parsing and representation across languages and frameworks
● Discourse markers and discourse relations (RST, PDTB, SDRT): Identification, prediction and extraction
● Attitudes discovery and interpretation in Discourse: Appraisal and sentiment
● Effects of multimodality on discourse interpretation: Intonation, gesture and text
● Interoperability for Multilingual language data: Challenges of rich and distributed data
● Discourse data and machine learning: Methods and tools
Discourse comprises a wide variety of linguistic phenomena, such as discourse markers, discourse relations, and speaker attitude, which have been largely studied by different communities of practice from Linguistics and Computation, rendering several theoretical frameworks (for instance, RST, SDRT, PDTB, for discourse relations; appraisal theory for sentiment analysis,...), and technological approaches, such as transformer models, embeddings and alike. Nonetheless, there are open issues concerning interoperability, multilinguality, and language processing, in particular, the existence of different annotation schemas, disambiguation, lack of training data for machine learning, scarcity of effective language phenomena detection and interpretation methods, diverse vocabularies, insufficient multilingual parallel corpora of non-dialogue and dialogue, initial stages of exploration of multimodality.
Discourse research is one of the central research areas of natural language processing (NLP) too. NLP research focuses on the formalisation, identification and discovery of semantic phenomena, dialogue exchange structure, and text coherence. Some of the technological approaches of NLP include the use of transformer models, word embeddings, linguistic linked open data, the constitution of aligned multilingual corpora, vocabularies of language phenomena and alike. Computational discourse explores the evidence that language consists not only of placing words in the right order but also of detecting and interpreting the meaning and deeper textual relations and organising ideas into a logical flow. The linguistic approaches study language phenomena referring to coherence and cohesiveness of discourse, lexical, phrasal, syntactic, semantic and pragmatic means to express discourse relations, represent their roles and build language resources for them.
Despite all the advances, there are still plenty of unresolved problems related to interoperability, multilinguality, and language processing. With the growth of the Semantic Web and Linguistic Linked Data, interoperability is key to reading, interpreting and adopting language resources. The existence of different annotation schemas to encode discourse relations constitutes a problem for data exchange and reuse and for theoretical consistency. The treatment of multilinguality is also complicated because of the insufficiency of multilingual parallel corpora of collections of non-dialogue and dialogue texts, which would allow systematic contrastive studies. As to language processing, the lack of training data for machine learning, coupled with the scarcity of effective language phenomena detection and interpretation methods, the coexistence of diverse vocabularies, and the minimal attention to the contribution of the tone of voice, intonation, gestures to the meaning and the informative value of discourse elements make the task of discourse processing still very challenging.
The workshop intends to be a discussion forum for researchers interested in addressing the aforementioned challenges and advancing the state-of-art in discourse studies and linguistic data science.
*Programme*
The Scientific Programme will include one invited talk and oral presentations.
Invited Speaker
Johan Bos, University of Groningen
*Submissions*
Submissions can be in the form of:
• long papers: 9–12 pages;
• short papers: 4–6 pages.
All submission lengths are given including references. Accepted submissions will be published by ACL in an open-access conference proceedings volume, free of charge for authors. The ACL templates should therefore be used for all conference submissions. As the reviewing process is single-blind, submissions should not be anonymised.
The workshop will be hybrid (face-to-face and remote). Note that at least one author of each accepted paper must register to present the paper at the workshop (either remotely or on-site). There will be no registration fee administered for participating in DiSLiDaS 2023.
Submissions must be submitted electronically via EasyChair:
https://easychair.org/conferences/?conf=dislidas2023
*Important dates*
Time Zone: Anywhere on Earth
Papers due: May, 19, 2023
Papers acceptance notifications: June, 16, 2023
Camera-ready papers due: June, 30, 2023
*Programme Committee*
Elena-Simona Apostol, University Politehnica of Bucharest, Romania
Harry Bunt, Tilburg University, Netherlands
Maria Josep Cuenca, Universitat de València
Debopam Das, Humboldt University of Berlin, Germany
Jorge Garcia, University of Zaragoza, Spain
Mikel Iruskieta, University of the Basque Country, Spain
António Leal, University of Porto, Portugal
Chaya Liebeskind, Jerusalem College of Technology, Israel
Amália Mendes, University of Lisbon, Portugal
Maciej Ogrodniczuk, Polish Academy of Sciences, Poland
Giedre Valunaite Oleskevicienė, Mykolas Romeris University, Lithuanian
Georg Rehm, DFKI GmbH, Germany
Ted Sanders, Utrecht University, Netherlands
Merel Scholman, University of Saarland, Germany
Dimitar Trajanov, Ss. Cyril and Methodius University, North Macedonia
Radoslava Trnavac, University of Belgrade, Serbia
Ciprian-Octavian Truica, University Politehnica of Bucharest, Romania
Amir Zeldes, The Georgetown University, USA
*Organising Committee*
Purificação Silvano, University of Porto, Portugal
Mariana Damova, Mozaika, Ltd., Bulgaria
Christian Chiarcos, Goethe-Universität, Germany
Anna Bączkowska, University of Gdansk, Poland
*Contact*
organizers(a)dislidas.mozajka.co<mailto:organizers@dislidas.mozajka.co><mailto:organizers@dislidas.mozajka.co>
[Apologies for cross-posting]
At the end in English.
EDICIÓN XXII PREMIO SEPLN A LA MEJOR TESIS DOCTORAL EN PROCESAMIENTO DEL LENGUAJE NATURAL
[Plazo de presentación: 2 de mayo de 2023]
La Sociedad Española para el Procesamiento del Lenguaje Natural convoca la Edición XXII del Premio SEPLN a la Mejor Tesis Doctoral en Procesamiento del Lenguaje Natural, que se regirá por las siguientes bases:
La finalidad de este premio es la promoción y divulgación de la investigación en el campo del procesamiento del lenguaje natural.
La tesis será premiada con una computadora portátil compacta (tablet). Se dará entrega del premio en el 39 Congreso Internacional de la Sociedad Española del Procesamiento del Lenguaje Natural (SEPLN 2023), tras una breve presentación del trabajo premiado por parte del autor.
Para poder concursar, el autor de la tesis doctoral debe ser socio de la SEPLN en el momento de presentar el trabajo. Ninguna persona concursante podrá participar como autora en más de un trabajo.
Se podrán presentar a concurso tesis doctorales leídas durante el año 2022, escritas en una lengua del Estado español o en lengua inglesa.
Además de la tesis completa, es imprescindible enviar:
Un breve resumen de 4 páginas donde claramente se indique el tema y la relevancia de la investigación, los objetivos, métodos, resultados alcanzados y contribuciones.
Una breve descripción de la trayectoria científica del autor de la tesis, en la que se describa la participación en actividades científicas como organización de de tareas competitivas, congresos, generación de recursos open access como conjuntos de datos, modelos de lenguaje, etc., y participación en proyectos, contratos, y/o patentes.
La calidad de la presentación, la corrección técnica y metodológica, la relevancia, originalidad, la generación, evaluación y publicación de recursos, así como la trayectoria investigadora durante el periodo predoctoral serán los criterios empleados para la adjudicación del premio por parte del jurado.
Los trabajos se enviarán a través de la web de la revista de la Sociedad (http://journal.sepln.org) en formato PDF antes del 2 de mayo de 2023.
La resolución del premio se comunicará durante el 39 Congreso Internacional de la Sociedad Española del Procesamiento del Lenguaje Natural (SEPLN 2023).
Documento con las instrucciones (aquí)
Para más información dirigirse a aitziber.atucha(a)ehu.eus
22nd EDITION OF THE SEPLN AWARD TO THE BEST DOCTORAL THESIS IN NATURAL LANGUAGE PROCESSING
[Submission deadline: May 2nd, 2023]
The Spanish Society for Natural Language Processing announces the 22 Edition of the SEPLN Award for the Best Doctoral Thesis in Natural Language Processing, which will be governed by the following bases:
The purpose of this award is the promotion and dissemination of research in the field of natural language processing.
The thesis will be awarded with a compact laptop (tablet). The award will be presented at the 39th International Congress of the Spanish Society for Natural Language Processing (SEPLN 2023), after a brief presentation of the award-winning work by the author.
In order to compete, the author of the doctoral thesis must be a member of the SEPLN at the time of submitting the work. No contestant may participate as an author in more than one work.
Doctoral theses read during the year 2023, written in a language of the Spanish State or in English, may be submitted to competition.
In addition to the complete thesis, it is essential to send:
a 4-page summary of the thesis, clearly describing the topic and the relevance of the research, the objectives, methods, results achieved and contributions.
a brief description of the scientific career of the author of the thesis, detailing the participation in scientific activities such as organization of competitive tasks, congresses, generation of open access resources such as sets of data, language models, etc., and participation in projects, contracts, and/or patents.
The quality of the presentation, the technical and methodological correctness, the relevance, originality, the generation, evaluation and publication of resources, as well as the research trajectory during the pre-doctoral period will be the criteria used for the award of the prize by the jury.
The works will be submitted through the website of the Society's magazine (http://journal.sepln.org) in PDF format before May 2nd 2023.
The final decision will be communicated during the 39th International Congress of the Spanish Society for Natural Language Processing (SEPLN 2023).
Submission instructions (http://www.sepln.org/sites/default/files/noticia/documentos_relacionados/20…)
For more information: aitziber.atucha(a)ehu.eus
Dear colleagues,
we have a new PhD vacancy in the field of speech- and text anonymization in the medical domain in Berlin, Germany.
The position is in the “Medinym” project of the department of Quality and Usability Labs of Berlin Institute of Technology.
We’re looking for a Researcher or Junior Researcher level, offer a 2 years contract with optional prolongation and PhD perspective.
Application deadline: Feb 28
More details and how to apply:
TU Berlin: https://www.jobs.tu-berlin.de/en/job-postings/161912
Please circulate upon potentially interested. Many thanks!
In case of questions pls contact me, I'm happy to help.
Best regards from Berlin,
Tim
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Dr.-Ing. Tim Polzehl
Associate Senior Researcher
Technische Universität Berlin
Quality and Usability Lab
Ernst-Reuter-Platz 7
D-10587 Berlin, Germany
Email: tim.polzehl(a)qu.tu-berlin.de
Web: www.qu.tu-berlin.de
Dear all,
We are excited to announce an open fulltime position for a researcher (phd possible, salary grade E 13 TV-L Berliner Hochschulen) in the field of speech signals analysis and assessment of speech quality in different mobile and fixed networks. The ideal candidate will have a passion for analyzing speech signals in listening-only and conversational situations, and will be responsible for developing signal-based and parametric models for the estimation of speech quality.
One of the main focuses of the research will be the evaluation of new speech codecs in different network scenarios. Additionally, the models will be validated based on subjective listening and conversation tests. For this purpose, methods of crowdsourcing can be applied, where real users will carry out data collection and/or evaluation via an online platform. It will be scientifically interesting to compare crowdsourced data to those obtained under laboratory conditions.
The position is located in Berlin, Germany at the Quality and Usability Lab of Technische Universität Berlin.
If you are interested in joining our team and have a background in speech signals analysis or quality assessment, please find the full job description provided under this link: https://tubcloud.tu-berlin.de/s/spSGFYipWsPsDBq .
We look forward to hearing from you!
Best regards,
Stefan Hillmann
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Dr.-Ing. Stefan Hillmann
(er/sein, he/his)
Wissenschaftlicher Mitarbeiter
Senior Researcher
Technische Universität Berlin
Fakultät IV, Elektrotechnik und Informatik
Quality and Usability Lab
EECS, Electrical Engineering and Computer Science
Quality and Usability Lab
Straße des 17. Juni 135, 10623 Berlin
GERMANY
stefan.hillmann(a)tu-berlin.de
https://tu.berlin/index.php?id=29495
ORCID: https://orcid.org/0000-0002-0795-9834https://www.tu.berlin/qu