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Found 16 papers, 11 papers with code
Modéliser la perception des genres musicaux à travers différentes cultures à partir de ressources linguistiques (Modeling the Music Genre Perception across Language-Bound Cultures )
Nous résumons nos travaux de recherche, présentés à la conférence EMNLP 2020 et portant sur la modélisation de la perception des genres musicaux à travers différentes cultures, à partir de représentations sémantiques spécifiques à différentes langues.
Detecting Synthetic Lyrics with Few-Shot Inference
In recent years, generated content in music has gained significant popularity, with large language models being effectively utilized to produce human-like lyrics in various styles, themes, and linguistic structures.
Improving Quotation Attribution with Fictional Character Embeddings
Humans naturally attribute utterances of direct speech to their speaker in literary works.
A Realistic Evaluation of LLMs for Quotation Attribution in Literary Texts: A Case Study of LLaMa3
In literary tasks, the performance of LLMs is often correlated to the degree of book memorization.
Distinguishing Fictional Voices: a Study of Authorship Verification Models for Quotation Attribution
Recent approaches to automatically detect the speaker of an utterance of direct speech often disregard general information about characters in favor of local information found in the context, such as surrounding mentions of entities.
Automatic Annotation of Direct Speech in Written French Narratives
The automatic annotation of direct speech (AADS) in written text has been often used in computational narrative understanding.
A Human Subject Study of Named Entity Recognition (NER) in Conversational Music Recommendation Queries
We conducted a human subject study of named entity recognition on a noisy corpus of conversational music recommendation queries, with many irregular and novel named entities.
Exploiting Device and Audio Data to Tag Music with User-Aware Listening Contexts
Namely, we propose a system which can generate a situational playlist for a user at a certain time 1) by leveraging user-aware music autotaggers, and 2) by automatically inferring the user's situation from stream data (e. g. device, network) and user's general profile information (e. g. age).
Explainability in Music Recommender Systems
In this article, we discuss how explainability can be addressed in the context of MRSs.
Collaborative Filtering
Explainable artificial intelligence
+3
Topic Modeling on Podcast Short-Text Metadata
Podcasts have emerged as a massively consumed online content, notably due to wider accessibility of production means and scaled distribution through large streaming platforms.
Probing Pre-trained Auto-regressive Language Models for Named Entity Typing and Recognition
The results show: auto-regressive language models as meta-learners can perform NET and NER fairly well especially for regular or seen names; name irregularity when often present for a certain entity type can become an effective exploitable cue; names with words foreign to the model have the most negative impact on results; the model seems to rely more on name than context cues in few-shot NER.
Modeling the Music Genre Perception across Language-Bound Cultures
The music genre perception expressed through human annotations of artists or albums varies significantly across language-bound cultures.
Cultural Vocal Bursts Intensity Prediction
Information Retrieval
+2
Multilingual Music Genre Embeddings for Effective Cross-Lingual Music Item Annotation
However, without a parallel corpus, previous solutions could not handle tag systems in other languages, being limited to the English-language only.
Muzeeglot : annotation multilingue et multi-sources d'entit\'es musicales \`a partir de repr\'esentations de genres musicaux (Muzeeglot : cross-lingual multi-source music item annotation from music genre embeddings)
Au sein de cette d{\'e}monstration, nous pr{\'e}sentons Muzeeglot, une interface web permettant de visualiser des espaces de repr{\'e}sentations de genres musicaux provenant de sources vari{\'e}es et de langues diff{\'e}rentes.
Leveraging Knowledge Bases And Parallel Annotations For Music Genre Translation
Here, we choose a new angle for the genre study by seeking to predict what would be the genres of musical items in a target tag system, knowing the genres assigned to them within source tag systems.
