Update: 05-02-2025

Author: cldocid2

science.md

@@ -0,0 +1,34 @@
+---
+
+copyright:
+  years: 2015, 2025
+lastupdated: "2025-02-05"
+
+subcollection: speech-to-text
+
+---
+
+{{site.data.keyword.attribute-definition-list}}
+
+# The science behind the service
+{: #science}
+
+{{site.data.keyword.IBM}} has been at the forefront of speech recognition research since the early 1960s. For example, [Bahl, Jelinek, and Mercer (1983)](https://ieeexplore.ieee.org/document/4767370){: external} describes the basic mathematical approach to speech recognition that is employed in essentially all modern speech recognition systems. And [Jelinek (1985)](https://ieeexplore.ieee.org/document/1457611){: external} describes the creation of the first real-time large vocabulary speech recognition system for dictation. This paper also describes problems that are still unsolved research topics today.
+{: shortdesc}
+
+{{site.data.keyword.IBM_notm}} continues this rich tradition of research and development with the {{site.data.keyword.speechtotextfull}} service. {{site.data.keyword.IBM_notm}} has demonstrated industry-record speech recognition accuracy on the public benchmark data sets for Conversational Telephone Speech (CTS) ([Saon and others, 2017](https://www.isca-speech.org/archive_v0/Interspeech_2017/pdfs/0405.PDF){: external}) and Broadcast News (BN) transcription ([Thomas and others, 2019](http://arxiv.org/pdf/1904.13258){: external}). {{site.data.keyword.IBM_notm}} leveraged neural networks for language modeling ([Kurata and others, 2017a](https://www.isca-speech.org/archive_v0/Interspeech_2017/pdfs/0723.PDF){: external}), and [Kurata and others, 2017b](http://arxiv.org/pdf/1709.06436){: external}, in addition to demonstrating the effectiveness of acoustic modeling.
+
+The following announcements summarize {{site.data.keyword.IBM_notm}}'s recent speech recognition accomplishments:
+
+-   [Reaching new records in speech recognition](https://www.ibm.com/products/speech-to-text){: external}
+-   [{{site.data.keyword.IBM_notm}} Breaks Industry Record for Conversational Speech Recognition by Extending Deep Learning Technologies](https://newsroom.ibm.com/){: external}
+-   [{{site.data.keyword.IBM_notm}} Sets New Transcription Performance Milestone on Automatic Broadcast News Captioning](https://research.ibm.com/blog){: external}
+-   [IBM Research AI Advances Speaker Diarization in Real Use Cases](https://research.ibm.com/blog){: external}
+-   [Advancing RNN Transducer Technology for Speech Recognition](https://arxiv.org/abs/2103.09935){: external}
+
+These accomplishments contribute to further advance {{site.data.keyword.IBM_notm}}'s speech services. Recent ideas that best fit the cloud-based {{site.data.keyword.speechtotextshort}} service include
+
+-   *For language modeling,* {{site.data.keyword.IBM_notm}} leverages a neural network-based language model to generate training text ([Suzuki and others, 2019](https://ieeexplore.ieee.org/document/8683481){: external}).
+-   *For acoustic modeling,* {{site.data.keyword.IBM_notm}} uses a fairly compact model to accommodate the resource limitations of the cloud. To train this compact model, {{site.data.keyword.IBM_notm}} uses "teacher-student training / knowledge distillation." Large and strong neural networks such as Long Short-Term Memory (LSTM), VGG, and the Residual Network (ResNet) are first trained. The output of these networks is then used as teacher signals to train a compact model for actual deployment ([Fukuda and others, 2017](https://www.isca-speech.org/archive_v0/Interspeech_2017/pdfs/0614.PDF){: external}).
+
+To further push the envelope, {{site.data.keyword.IBM_notm}} also focuses on end-to-end modeling. For example, it has established a strong modeling pipeline for direct acoustic-to-word models ([Audhkhasi and others, 2017](https://www.isca-speech.org/archive_v0/Interspeech_2017/pdfs/0546.PDF){: external}, and [Audhkhasi and others, 2018](http://arxiv.org/pdf/1712.03133){: external}) that it is now further improving ([Saon and others, 2019](https://ieeexplore.ieee.org/document/8683706){: external}). It is also making efforts to create compact end-to-end models for future deployment on the cloud ([Kurata and Audhkhasi, 2019](http://arxiv.org/pdf/1904.08311){: external}).

toc.yaml

@@ -132,6 +132,10 @@ toc:
           - information-security.md
           - include: ../watson/service-endpoints.md
           - include: ../watson/virtual-endpoints.md
+      - topicgroup:
+          label: Service background
+          topics:
+          - science.md
   - navgroup:
       id: reference
       topics: