Searching In Audio Podcasts
TMCnet.com and Businesswire both mention a new audio search engine by PodZinger.com. (The Businesswire text is a press release). (Links below).
This is a fascinating idea become reality. Apparently, PodZinger is "based on 30 years of speech recognition research" from BBN Technologies. PodZinger first converts audio podcasts into text, then builds an index of keywords. When a user searches for certain words or phrases, related keywords are presented with visual cues, including "the text surrounding the search term".
As a test, I searched for the specific phrase "U2 concert", got two results, clicked on the second one, and heard a fragment of a podcast with two DJs discussing a U2 concert. I did another test using "poker playing". This returned several results. I clicked on the first result, then waited while the engine skimmed through the audio until about 18 minutes in.
What I found in both cases, though, is that even reasonable quality audio is sometimes not translated to text properly. But that's to be expected, given the multitudes of speech patterns. This technology needs to mature, and the neural network software continually trained. It'll be a while before software can translate audio of a single language perfectly. Let's face it, even humans have trouble understanding each other, let alone the semantics of what's being said.
If you ask me, though, this technology could be a key element in the quest for a universal language translator. The next step after converting English-language audio to text is to convert the text to another language, then to audio in the second language. Bravo, PodZinger and .
Links/Sources: PodZinger, TMCnet - Laura Stotler - PodZinger Search Engine Finds Spoken Keywords in Podcasts, BusinessWire - PodZinger Makes Podcast Searching Fast, Easy and Accurate, BBN Technologies Avoke STX Speech-To-Text Software.
(c) Copyright: 2006-present, Raj Kumar Dash, http://webguru.mathgurusonline.com/tech-watch/
Technorati Tags: audio search, search engine, speech to text, universal translator
This is a fascinating idea become reality. Apparently, PodZinger is "based on 30 years of speech recognition research" from BBN Technologies. PodZinger first converts audio podcasts into text, then builds an index of keywords. When a user searches for certain words or phrases, related keywords are presented with visual cues, including "the text surrounding the search term".
As a test, I searched for the specific phrase "U2 concert", got two results, clicked on the second one, and heard a fragment of a podcast with two DJs discussing a U2 concert. I did another test using "poker playing". This returned several results. I clicked on the first result, then waited while the engine skimmed through the audio until about 18 minutes in.
What I found in both cases, though, is that even reasonable quality audio is sometimes not translated to text properly. But that's to be expected, given the multitudes of speech patterns. This technology needs to mature, and the neural network software continually trained. It'll be a while before software can translate audio of a single language perfectly. Let's face it, even humans have trouble understanding each other, let alone the semantics of what's being said.
If you ask me, though, this technology could be a key element in the quest for a universal language translator. The next step after converting English-language audio to text is to convert the text to another language, then to audio in the second language. Bravo, PodZinger and .
Links/Sources: PodZinger, TMCnet - Laura Stotler - PodZinger Search Engine Finds Spoken Keywords in Podcasts, BusinessWire - PodZinger Makes Podcast Searching Fast, Easy and Accurate, BBN Technologies Avoke STX Speech-To-Text Software.
(c) Copyright: 2006-present, Raj Kumar Dash, http://webguru.mathgurusonline.com/tech-watch/
Technorati Tags: audio search, search engine, speech to text, universal translator
