The podcast dataset contains about 100k podcasts filtered to contain only documents which the creator tags as being in the English language, as well as by a language filter applied to the creator-provided title and description. We expect that there will be a small amount of multilingual content that may have slipped through these filters.

Episodes were sampled from both professional and amateur podcasts including:
Episodes produced in a studio with dedicated equipment by trained professionals
Episodes self-published from a phone app — these vary in quality depending on professionalism and equipment of the creator.

The episodes represent a wide range of:

• Audio quality: we can expect professionally produced podcasts to have high audio quality, but there is significant variability in the amateur podcasts. We have included a basic popularity filter to remove most podcasts that are defective or noisy.
• Topics: the episodes represent a wide range of topics, both coarse- and fine-grained. These include lifestyle and culture, storytelling, sports and recreation, news, health, documentary, and commentary.
• Formats: podcasts are structured in a number of different ways. These include scripted and unscripted monologues, interviews, conversations, debate, and included clips of other non-speech audio material.

The podcast dataset contains about 100k podcasts filtered to contain only documents which the creator tags as being in the English language, as well as by a language filter applied to the creator-provided title and description. We expect that there will be a small amount of multilingual content that may have slipped through these filters.

Episodes were sampled from both professional and amateur podcasts including episodes produced in a studio with dedicated equipment by trained professionals, as well as episodes self-published from a phone app — these vary in quality depending on professionalism and equipment of the creator.

The episodes represent a wide range of:

• Audio quality: we can expect professionally produced podcasts to have high audio quality, but there is significant variability in the amateur podcasts. We have included a basic popularity filter to remove most podcasts that are defective or noisy.
• Topics: the episodes represent a wide range of topics, both coarse- and fine-grained. These include lifestyle and culture, storytelling, sports and recreation, news, health, documentary, and commentary.
• Structural formats: podcasts are structured in a number of different ways. These include scripted and unscripted monologues, interviews, conversations, debate, and included clips of other non-speech audio material.

Each of the 100,000 episodes in the dataset includes an audio file, a text transcript, and some associated metadata. 

The data are separated into three top-level directories:

• one for transcripts, one for RSS files, and one for audio data.
• Since the audio files are vastly larger than the metadata, and not all researchers will choose to work on the audio data, we make these available for separate download.
• The metadata can be found in a single csv file in the top-level directory

Audio directory:

OGG format available for separate download

Median duration of an episode ~ 31.6 minutes
Estimated size: ~2 TB for entire audio data set

Metadata:

Extracted basic metadata file in TSV format with fields: show_uri, show_name, show_description, publisher, language, rss_link, episode_uri, episode_name, episode_description, duration

Subdirectory for the episode RSS header files:

~1000 words with additional fields of potential interest, not necessarily aligned for every episode: channel, title, description, author, link, copyright, language, image
Estimated size: 145MB total for entire RSS set when compressed. 

Subdirectory for transcripts: 

JSON format
Average length is just under 6000 words, ranging from a small number of extremely short episodes to up to 45,000 words. Two-thirds of the transcripts are between about 1,000 and about 10,000 words in length; about 1% or 1,000 episodes are very short trailers to advertise other content. 
Estimated size: 12GB for entire transcript set
 

Example of Transcript:

The transcripts consist of a JSON structure. The below figure demonstrates the "results" structure which begins with a list of transcriptions of 30 second chunks of speech, each such chunk with a confidence score and with every word annotated with "startTime" and "endTime". The last item in the "results" structure is a list of all words for the entire episode, again with with "startTime" and "endTime" and in addition an inferred "speakerTag" to distinguish episode participants. While the "results" structure is designed to accommodate several hypotheses through its "alternatives" list structure, this present transcription does not provide alternative transcription hypotheses.

  {"results":  

 [{"alternatives":  // always only one alternative in these transcripts

   [{"transcript": "Hello, y'all, ... <30 s worth of text> ... ",

     "confidence": 0.8640950322151184,

     "words":  // list of words

     [{"startTime": "3s", "endTime": "3.300s", "word": "Hello,"}, 

... 

]}]},

  {"alternatives": [

      {"transcript": "Aaron ... ",

       "confidence": 0.7733442187309265,

       "words": [

  {"startTime": "30s", "endTime": "30.200s", "word": "Aaron"}, ... ]}]},

  {"alternatives":  // last item in "results": a straight list of words with "speakerTag"

   [{"words":

     [{"startTime": "3s", "endTime": "3.300s", "word": "Hello,", "speakerTag": 1},

      ...

{"startTime": "30s", "endTime": "30.200s", "word": "Aaron", "speakerTag": 1},

      ...

      {"startTime": "39.900s", "endTime": "40.500s", "word": "salon.", "speakerTag": 2} ] }] }]

}