Target Language Extraction at Multilingual Cocktail Parties

Typically, target speaker extraction seeks to extract a target speaker's contribution according to his or her individual voice characteristics. In a “multilingual cocktail party” however, listeners may desire to extract speaker contributions spoken in a particular language, regard-less of the number of contributing speakers. In this paper, we pro-pose a novel task called “target language extraction” (TLE) which extracts voices based on the spoken language rather than on individ-ual speaker characteristics. We introduce a new database for TLE which simulates the multilingual cocktail party problem in mixtures of two and four speakers with German as the target language. The database is derived from the GlobalPhone 2000 Speaker Package and is called “GlobalPhone Multilingual Cocktail Party - German” (GlobalPhoneMCP-GE). Our experimental results show that our approach to TLE achieves very good performance regardless of the number of speakers in the mixture and that TLE generalizes well to unseen speakers and interfering languages. This work represents the first attempt at target language extraction.