<p>The most suited NLP technique for this is probably <em>language models</em>.
They predict the likelihood of a word given the previous words (or surrounding words).
They can be used for error correction .<br>
You may find following useful:<br>
<a href="https://arxiv.org/pdf/1902.07178.pdf" rel="nofollow noreferrer">article</a><br>
<a href="https://medium.com/@davidmasse8/predicting-the-next-word-back-off-language-modeling-8db607444ba9" rel="nofollow noreferrer">page</a></p>
aligning sentences to corpus and finding mismatches
<p>The ideal goal is to correct the output from a speech2text model according to a reference corpus (the actual text). I don't mind using any off the selves tool either in NLP space or ElasticSearch </p>

<p>I have a reference corpus like the following:</p>

<blockquote>
  <p>It is a reliance that has led to a cycle of addiction that has
  destroyed lives it <strong>is a cycle that makes you sick when</strong> you <strong>try to stop
  and potentially takes your</strong> <strong>life when you don't and beyond</strong> its physical
  effects this cycle of addiction also includes constant contact with
  the criminal justice system and not just a cycle of arrests release
  and violation.</p>
</blockquote>

<p>In fact its much longer ...</p>

<p>On the other hand, I have a set of sentences that are recognized from a speech-2-text model in a CSV files</p>

<pre><code>1, is a cycle that makes you dick when
2, try two stops and essentially hates your
3, posses activated
4, lives when who don't and beyond
</code></pre>

<p>As you can see there because the speech2text model is not perfect there are errors, for example</p>

<p>1) With references to the corpus these subsentences are misspelled (e.g. dick instead of sick in number the sentence number 1
2) there are sentences that do not match to the corpus at all - e.g. number 3
3) putting the sentences together does not cover the whole paragraph.</p>

<p>So basically I wonder what is this task called in the NLP topic, then I can do a better googling, and I appreciate if you name specific functions or examples that I can leverage, e.g. in Space or NLTK or any other tool.</p>

<p><em>edit</em> : * I already have experience with nlp (coursera certificate) - therefore, looking for a concrete answer and/or example rather a scientific paper. This is not a general error correction task or the next work recommendation based on sequential models. </p>