tech,25-1-H92-1095,bq |
document processing
</term>
, integrating
<term>
|
language
|
understanding
</term>
with
<term>
speech recognition
|
#19662
Language understanding work at Paramax focuses on applying general-purpose language understanding technology to spoken language understanding, text understanding, and document processing, integratinglanguage understanding with speech recognition, knowledge-based information retrieval and image understanding. |
other,12-1-A94-1017,bq |
( APs )
</term>
for
<term>
real-time spoken
|
language
|
translation
</term>
.
<term>
Spoken language
|
#20207
This paper proposes a model using associative processors (APs) for real-time spoken language translation. |
other,0-2-A94-1017,bq |
language translation
</term>
.
<term>
Spoken
|
language
|
translation
</term>
requires ( 1 ) an accurate
|
#20211
Spoken language translation requires (1) an accurate translation and (2) a real-time response. |
other,14-9-A94-1017,bq |
meets the vital requirements of
<term>
spoken
|
language
|
translation
</term>
.
<term>
Japanese texts
|
#20363
Thus, our model, TDMT on APs, meets the vital requirements of spoken language translation. |
other,15-6-C94-1026,bq |
which are selected from different
<term>
|
language
|
families
</term>
. In
<term>
optical character
|
#20610
Most importantly, the experimental objects are Chinese-English texts, which are selected from differentlanguage families. |
other,10-1-C94-1030,bq |
speech recognition
</term>
of a
<term>
natural
|
language
|
</term>
, it has been difficult to detect
|
#20624
In optical character recognition and continuous speech recognition of a natural language, it has been difficult to detect error characters which are wrongly deleted and inserted. |
tech,4-1-C94-1061,bq |
<term>
concurrent , object-oriented natural
|
language
|
parsing
</term>
is introduced . Complete
<term>
|
#20821
A grammar model for concurrent, object-oriented natural language parsing is introduced. |
model,6-1-H94-1014,bq |
paper introduces a simple mixture
<term>
|
language
|
model
</term>
that attempts to capture
<term>
|
#21217
This paper introduces a simple mixturelanguage model that attempts to capture long distance constraints in a sentence or paragraph. |