  Spoken language translation (SLT) is becoming more important in the
increasingly globalized world, both from a social and economic point of view.
It is one of the major challenges for automatic speech recognition (ASR) and
machine translation (MT), driving intense research activities in these areas.
While past research in SLT, due to technology limitations, dealt mostly with
speech recorded under controlled conditions, today's major challenge is the
translation of spoken language as it can be found in real life. Considered
application scenarios range from portable translators for tourists, lectures
and presentations translation, to broadcast news and shows with live
captioning. We would like to present PJIIT's experiences in the SLT gained from
the Eu-Bridge 7th framework project and the U-Star consortium activities for
the Polish/English language pair. Presented research concentrates on ASR
adaptation for Polish (state-of-the-art acoustic models: DBN-BLSTM training,
Kaldi: LDA+MLLT+SAT+MMI), language modeling for ASR & MT (text normalization,
RNN-based LMs, n-gram model domain interpolation) and statistical translation
techniques (hierarchical models, factored translation models, automatic casing
and punctuation, comparable and bilingual corpora preparation). While results
for the well-defined domains (phrases for travelers, parliament speeches,
medical documentation, movie subtitling) are very encouraging, less defined
domains (presentation, lectures) still form a challenge. Our progress in the
IWSLT TED task (MT only) will be presented, as well as current progress in the
Polish ASR.
