Multilingual Corpora Annotation for Processing Definite Descriptions. - Renata Vieira; Susanne Salmon-Alt; Emmanuel Schang (PorTAL, 2002)

Describing São Tomense Using a Tree-Adjoining Meta-Grammar. - Emmanuel Schang; Denys Duchier; Brunelle Magnana Ekoukou; Yannick Parmentier 001; Simon Petitjean (TAG, 2012)

ANCOR, the first large French speaking corpus of conversational speech annotated in coreference to be freely available (ANCOR, premier corpus de français parlé d'envergure annoté en coréférence et distribué librement) [in French]. - Judith Muzerelle; Anaïs Lefeuvre; Jean-Yves Antoine; Emmanuel Schang; Denis Maurel; Jeanne Villaneau; Iris Eshkol (TALN (2), 2013)

ANCOR_Centre, a large free spoken French coreference corpus: description of the resource and reliability measures. - Judith Muzerelle; Anaïs Lefeuvre; Emmanuel Schang; Jean-Yves Antoine; Aurore Pelletier; Denis Maurel; Iris Eshkol; Jeanne Villaneau (LREC, 2014)

Tense and Time Annotations : a Contribution to TimeML Improvement (Annotation de la temporalité en corpus : contribution à l'amélioration de la norme TimeML) [in French]. - Anaïs Lefeuvre; Jean-Yves Antoine; Agata Savary; Emmanuel Schang; Lotfi Abouda; Denis Maurel; Iris Eshkol (TALN (2), 2014)

Covering various Needs in Temporal Annotation: a Proposal of Extension of ISO TimeML that Preserves Upward Compatibility. - Anaïs Lefeuvre-Halftermeyer; Jean-Yves Antoine; Alain Couillault; Emmanuel Schang; Lotfi Abouda; Agata Savary; Denis Maurel; Iris Eshkol-Taravella; Delphine Battistelli (LREC, 2016)

Automatic Speech Recognition and Query By Example for Creole Languages Documentation. - Cécile Macaire; Didier Schwab; Benjamin Lecouteux; Emmanuel Schang (ACL (Findings), 2022)

Technologies de la parole et données de terrain : le cas du créole haïtien. - William N. Havard; Renauld Govain; Daphne Gonçalves Teixeira; Benjamin Lecouteux; Emmanuel Schang (TALN (1), 2024)

Self-Supervised Models of Speech Processing for Haitian Creole. - William N. Havard; Renauld Govain; Benjamin Lecouteux; Emmanuel Schang (INTERSPEECH, 2025)