This paper presents the acquisition and annotation of Slovenian Lombard Speech Database, the recording of which started in the year 2008. The database was recorded at the University of Maribor, Slovenia. The goal of this paper is to describe the hardware platform used for the acquisition of speech material, recording scenarios and tools used for the annotation of Slovenian Lombard Speech Database. The database consists of recordings of 10 Slovenian native speakers. Five males and five females were recorded. Each speaker pronounced a set of eight corpuses in two recording sessions with at least one week pause between recordings. The structure of the corpus is similar to SpeechDat II database. Approximately 30 minutes of speech material per speaker and per session was recorded. The manual annotation of speech material is performed with the LombardSpeechLabel tool developed at the University of Maribor. The speech and annotation material was saved on 10 DVDs (one speaker on one DVD).

The consortium ECESS (European Center of Excellence for Speech Synthesis) has set up a framework for evaluation of software modules and tools relevant for speech synthesis. Till now two lines of evaluation campaigns have been established: (1) Evaluation of the ECESS TTS modules (text processing, prosody, acoustic synthesis). (2) Evaluation of ECESS tools (pitch extraction, voice activity detection, phonetic segmentation). The functionality and interfaces of the ECESS TTS have been developed by a joint effort between ECESS and the EC-funded project TC-STAR . First evaluation campaigns were conducted within TC-STAR using the ECESS framework. As TC-STAR finished in March 2007, ECESS continued and extended the evaluation of ECESS TTS modules and tools by its own. Within the paper we describe a novel framework which allows performing remote evaluation for modules via the web. First experimental results are reported. Further the result of several evaluation campaigns for tools handling pitch extraction and voice activity detection are presented.

This paper presents the SINOD database, which is the first Slovenian non-native speech database. It will be used to improve the performance of large vocabulary continuous speech recogniser for non-native speakers. The main quality impact is expected for acoustic models and recogniser’s vocabulary. The SINOD database is designed as supplement to the Slovenian BNSI Broadcast News database. The same BN recommendations were used for both databases. Two interviews with non-native Slovenian speakers were incorporated in the set. Both non-native speakers were female, whereas the journalist was Slovenian native male speaker. The transcription approach applied in the production phase is presented. Different statistics and analyses of database are given in the paper.