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	<id>https://openvoice-tech.net/api.php?action=feedcontributions&amp;feedformat=atom&amp;user=Digitalica</id>
	<title>Open Voice Technology Wiki - User contributions [en]</title>
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	<link rel="alternate" type="text/html" href="https://openvoice-tech.net/wiki/Special:Contributions/Digitalica"/>
	<updated>2026-05-08T14:54:17Z</updated>
	<subtitle>User contributions</subtitle>
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	<entry>
		<id>https://openvoice-tech.net/index.php?title=Glossary_of_voice_tech&amp;diff=2191</id>
		<title>Glossary of voice tech</title>
		<link rel="alternate" type="text/html" href="https://openvoice-tech.net/index.php?title=Glossary_of_voice_tech&amp;diff=2191"/>
		<updated>2022-01-03T22:02:09Z</updated>

		<summary type="html">&lt;p&gt;Digitalica: add intent&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;[[Category:Open Voice Tech]]&lt;br /&gt;
&lt;br /&gt;
In the field of voice technology there are lots of buzzwords. Some are self explaining, other lead to confusion regularly. This list should be a glossary.&lt;br /&gt;
&lt;br /&gt;
==General terms==&lt;br /&gt;
&lt;br /&gt;
*[[:Category:Dataset|Dataset]]&lt;br /&gt;
*[[Research papers|Papers]] (&#039;&#039;research papers&#039;&#039;)&lt;br /&gt;
*[[Phonemes]]&lt;br /&gt;
*[[Model]]&lt;br /&gt;
*[[Checkpoint]]&lt;br /&gt;
*[[Repository]]&lt;br /&gt;
&lt;br /&gt;
==STT terms==&lt;br /&gt;
&lt;br /&gt;
*[[:Category:Wake words|Wake word]]&lt;br /&gt;
*[[Hotword]]&lt;br /&gt;
*[[Voice print]]&lt;br /&gt;
*[[Word error rate]] (&#039;&#039;WER&#039;&#039;)&lt;br /&gt;
*[[Diarization]]&lt;br /&gt;
*[[Barge-in]]&lt;br /&gt;
&lt;br /&gt;
==TTS terms==&lt;br /&gt;
&lt;br /&gt;
*&lt;br /&gt;
&lt;br /&gt;
==Voice assistant terms==&lt;br /&gt;
&lt;br /&gt;
*[[Conversational AI]]&lt;br /&gt;
*[[Natural language understanding]] (&#039;&#039;NLU&#039;&#039;)&lt;br /&gt;
*[[Intent]]&lt;br /&gt;
*[[Utterance]]&lt;br /&gt;
*[[Voiceonly]]&lt;br /&gt;
&lt;br /&gt;
==Machine learning==&lt;br /&gt;
&lt;br /&gt;
*[[Epoch]]&lt;br /&gt;
*[[Step]]&lt;br /&gt;
*[[Batch size]]&lt;br /&gt;
*[[Learning rate]]&lt;br /&gt;
*[[Inference]]&lt;br /&gt;
*[[Alignment]]&lt;/div&gt;</summary>
		<author><name>Digitalica</name></author>
	</entry>
	<entry>
		<id>https://openvoice-tech.net/index.php?title=Natural_language_understanding&amp;diff=2190</id>
		<title>Natural language understanding</title>
		<link rel="alternate" type="text/html" href="https://openvoice-tech.net/index.php?title=Natural_language_understanding&amp;diff=2190"/>
		<updated>2022-01-03T21:56:32Z</updated>

		<summary type="html">&lt;p&gt;Digitalica: add links&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;Natural Language Understanding (NLU) is a a misleading term, highly discussed in the Conversational AI / scientific community.&lt;br /&gt;
&lt;br /&gt;
In recent years, especially in the [[chatbot]] engineering industry, we tend to use NLU to mean an [[intent]]/entities classifier, based on machine learning techniques (transformers, etc.). The main open source project / state of the art of this approach is probably the [https://rasa.com/blog/introducing-dual-intent-and-entity-transformer-diet-state-of-the-art-performance-on-a-lightweight-architecture/ RASA DIET classifier].&lt;br /&gt;
&lt;br /&gt;
Besides, in terms of linguistic, and psycho-linguistic/cognitive scientific disciplines, there is a great skepticism about naming &amp;quot;language understanding&amp;quot; a ML-based classifier of intents (and entities). A growing number of researcher linguists state that it&#039;s even impossible to understand language with machine language techniques (the more famous and currently debated is probably [[GPT-3]]). One of the scientist more active in this battle is [https://ontologik.medium.com/ Walid Saba].&lt;/div&gt;</summary>
		<author><name>Digitalica</name></author>
	</entry>
	<entry>
		<id>https://openvoice-tech.net/index.php?title=Python&amp;diff=2189</id>
		<title>Python</title>
		<link rel="alternate" type="text/html" href="https://openvoice-tech.net/index.php?title=Python&amp;diff=2189"/>
		<updated>2022-01-03T21:52:24Z</updated>

		<summary type="html">&lt;p&gt;Digitalica: cleanup, add link.&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;Python is a programming Language. Wikipedia says:&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
&#039;&#039;&#039;Python&#039;&#039;&#039; is an interpreted high-level general-purpose programming language. Its design philosophy emphasizes code readability with its use of significant indentation. Its language constructs as well as its object-oriented approach aim to help programmers write clear, logical code for small and large-scale projects.&lt;br /&gt;
&lt;br /&gt;
The language was developed by Guido van Rossum in the late 80&#039;s. Python 2.0 was released in 2000, Python 3.0 - with some mayor changes - in 2008. Since 2020, Python 2 is no longer supported. Python is supported on almost every platform, and easy to learn. Therefore, it is used widely.&lt;br /&gt;
&lt;br /&gt;
== External links ==&lt;br /&gt;
&lt;br /&gt;
* https://www.python.org/&lt;/div&gt;</summary>
		<author><name>Digitalica</name></author>
	</entry>
	<entry>
		<id>https://openvoice-tech.net/index.php?title=Python&amp;diff=2188</id>
		<title>Python</title>
		<link rel="alternate" type="text/html" href="https://openvoice-tech.net/index.php?title=Python&amp;diff=2188"/>
		<updated>2022-01-03T21:40:02Z</updated>

		<summary type="html">&lt;p&gt;Digitalica: first version of Python page&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;Python is a programming Language. Wikipedia says:&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
&#039;&#039;&#039;Python&#039;&#039;&#039; is an interpreted high-level general-purpose programming language. Its design philosophy emphasizes code readability with its use of significant indentation. Its language constructs as well as its object-oriented approach aim to help programmers write clear, logical code for small and large-scale projects.&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
The language was developed by Guido van Rossum in the late 80&#039;s. Python 2.0 was released in 2000, Python 3.0 - with some mayor changes - in 2008. Since 2020, Python 2 is no longer supported. Python is supported on almost every platform, and easy to learn. Therefore, it is used widely.&lt;/div&gt;</summary>
		<author><name>Digitalica</name></author>
	</entry>
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