<instructions>Your goal is to analyze the following comment and estimate how highly it will be upvoted by the Hacker News community.</instructions><comment><author>buss</author><text>Google voice search also has anaphora, or backreferences to previous searches. For example voice search for &amp;quot;Who was the first president of the United States?&amp;quot; then after you get the result do another voice search for &amp;quot;Who was his vice president?&amp;quot; and Google will infer you are still talking about George Washington.&lt;p&gt;One step closer to conversational interfaces!</text><parent_chain></parent_chain></comment><story><title>Google voice search: faster and more accurate</title><url>http://googleresearch.blogspot.com/2015/09/google-voice-search-faster-and-more.html</url></story>
<instructions>Your goal is to analyze the following comment and estimate how highly it will be upvoted by the Hacker News community.</instructions><comment><author>nl</author><text>The paper describing this work: &lt;a href=&quot;http:&amp;#x2F;&amp;#x2F;arxiv.org&amp;#x2F;pdf&amp;#x2F;1507.06947v1.pdf&quot; rel=&quot;nofollow&quot;&gt;http:&amp;#x2F;&amp;#x2F;arxiv.org&amp;#x2F;pdf&amp;#x2F;1507.06947v1.pdf&lt;/a&gt;&lt;p&gt;They trained on 3 million &amp;quot;utterances&amp;quot; of average duration of 4 seconds. These were distorted by noise to get 20 variations (so the training set was 60 million utterances total).&lt;p&gt;I don&amp;#x27;t understand if these were labeled somehow There&amp;#x27;s a section on clustering into 9287 phones, but it isn&amp;#x27;t clear to me if these were used as labels.</text><parent_chain></parent_chain></comment><story><title>Google voice search: faster and more accurate</title><url>http://googleresearch.blogspot.com/2015/09/google-voice-search-faster-and-more.html</url></story>