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Dear Dominika,</div>
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I've used Pinpoint and Express Scribe for transcription and they work quite well. My colleagues tell me Otter.ai and TurboScribe also work well, though I have not tried those. </div>
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Good luck!</div>
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Maria Lis</div>
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<b>From:</b> Linganth <linganth-bounces@listserv.linguistlist.org> on behalf of linganth-request@listserv.linguistlist.org <linganth-request@listserv.linguistlist.org><br>
<b>Sent:</b> Thursday, April 9, 2026 17:30<br>
<b>To:</b> linganth@listserv.linguistlist.org <linganth@listserv.linguistlist.org><br>
<b>Subject:</b> Linganth Digest, Vol 139, Issue 13</div>
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Today's Topics:<br>
<br>
   1. Re: Recommendations for tools transcribing and analyzing<br>
      large amounts of data (Kathe Managan)<br>
   2. Re: [EXT] Re: Recommendations for tools transcribing and<br>
      analyzing large amounts of data (Dominika Baran, Ph.D.)<br>
<br>
<br>
----------------------------------------------------------------------<br>
<br>
Message: 1<br>
Date: Thu, 9 Apr 2026 20:01:20 +0000<br>
From: Kathe Managan <kathe.managan@louisiana.edu><br>
To: "Dominika Baran, Ph.D." <dominika.baran@duke.edu>, "Linguistic<br>
        Anthropology Discussion Group (LINGANTH@listserv.linguistlist.org)"<br>
        <linganth@listserv.linguistlist.org><br>
Subject: Re: [Linganth] Recommendations for tools transcribing and<br>
        analyzing large amounts of data<br>
Message-ID:<br>
        <PH0PR22MB253408F24F85527553B721E6FD582@PH0PR22MB2534.namprd22.prod.outlook.com><br>
       <br>
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<br>
Hi Dominika,<br>
<br>
I recently switched to Trint for a big project. It works in 40 different languages and has good accuracy. It also has robust privacy and security features.<br>
<br>
Best,<br>
Kathe<br>
<br>
Get Outlook for iOS<<a href="https://aka.ms/o0ukef" data-auth="NotApplicable" id="OWA4ced639c-4cb8-f5ee-0eb2-36d8dcd90c26" class="OWAAutoLink">https://nam12.safelinks.protection.outlook.com/?url=https%3A%2F%2Faka.ms%2Fo0ukef&data=05%7C02%7Cbaiocchiml%40pitt.edu%7C1eb154ffe5b547886dd608de9676e943%7C9ef9f489e0a04eeb87cc3a526112fd0d%7C1%7C0%7C639113634665607199%7CUnknown%7CTWFpbGZsb3d8eyJFbXB0eU1hcGkiOnRydWUsIlYiOiIwLjAuMDAwMCIsIlAiOiJXaW4zMiIsIkFOIjoiTWFpbCIsIldUIjoyfQ%3D%3D%7C0%7C%7C%7C&sdata=681XD9iMoFpTo7YZmXATdDvz0xL2R9Ch%2BY46HNalk0c%3D&reserved=0</a>><br>
________________________________<br>
From: Linganth <linganth-bounces@listserv.linguistlist.org> on behalf of Dominika Baran, Ph.D. <dominika.baran@duke.edu><br>
Sent: Thursday, April 9, 2026 2:01:58 PM<br>
To: Linguistic Anthropology Discussion Group (LINGANTH@listserv.linguistlist.org) <linganth@listserv.linguistlist.org><br>
Subject: [Linganth] Recommendations for tools transcribing and analyzing large amounts of data<br>
<br>
CAUTION: This email originated from outside of UL Lafayette. Do not click links or open attachments unless you recognize the sender and know the content is safe.<br>
<br>
Dear Colleagues,<br>
<br>
I am looking for recommendations of your favorite tool(s), at the moment, for processing large amounts of recorded spoken & written conversational data (informal interviews, free conversations), for both transcription and coding & analysis.<br>
<br>
I have about 100 hours of digitally recorded conversations, including those among multiple speakers, with lots of simultaneous speech, two conversations going on at once, overlap, and code-switching (mostly bilingual, occasionally trilingual). I also have 13
 years of written group chat conversations, which don?t need transcribing but it is over 300,000 words. I am looking for suggestions for software, online or otherwise, for both transcription (which is tricky because of the multilingual and overlapping conversations)
 and, more importantly, organization, coding, and analysis. It has been a while since I have dealt with THIS much data and I am sure there is a lot out there that I don?t know about - all and any suggestions of what has worked for folks are very much appreciated!<br>
<br>
Best,<br>
Dominika<br>
<br>
<br>
<br>
Dominika M. Baran<br>
<br>
Associate Professor<br>
<br>
English Department<br>
<br>
Duke University<br>
<br>
Allen Building 303<br>
<br>
Durham, NC 27708<br>
<br>
<br>
<br>
Pronouns: she/her/hers<br>
<br>
<br>
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------------------------------<br>
<br>
Message: 2<br>
Date: Thu, 9 Apr 2026 20:30:47 +0000<br>
From: "Dominika Baran, Ph.D." <dominika.baran@duke.edu><br>
To: "Roth-Gordon, Jen - (jenrothg)" <jenrothg@arizona.edu>,<br>
        "linganth@listserv.linguistlist.org"<br>
        <linganth@listserv.linguistlist.org><br>
Subject: Re: [Linganth] [EXT] Re: Recommendations for tools<br>
        transcribing and analyzing large amounts of data<br>
Message-ID:<br>
        <DM6PR05MB4572F5003B7AFC4D7F41AE48ED582@DM6PR05MB4572.namprd05.prod.outlook.com><br>
       <br>
Content-Type: text/plain; charset="utf-8"<br>
<br>
Hi Jen,<br>
<br>
Yes!! That?s exactly what happened here! Who knew in 2013 that? etc.<br>
<br>
Best,<br>
Dominika<br>
<br>
<br>
Dominika M. Baran<br>
Associate Professor<br>
English Department<br>
Duke University<br>
Allen Building 303<br>
Durham, NC 27708<br>
<br>
Pronouns: she/her/hers<br>
<br>
From: Linganth <linganth-bounces@listserv.linguistlist.org> on behalf of Roth-Gordon, Jen - (jenrothg) <jenrothg@arizona.edu><br>
Date: Thursday, April 9, 2026 at 3:58?PM<br>
To: linganth@listserv.linguistlist.org <linganth@listserv.linguistlist.org><br>
Subject: Re: [Linganth] [EXT] Re: Recommendations for tools transcribing and analyzing large amounts of data<br>
<br>
Re: "I'm curious, how do you end up with so much data without first thinking<br>
about how you will handle it?"<br>
<br>
Funny! I think many of us find ourselves swimming in data and notes that would fill rooms if printed out (especially for long-term projects). While overwhelming, that would be my definition of a successful research project!<br>
<br>
Sending solidarity (in lieu of concrete tech suggestions),<br>
jen<br>
<br>
Jennifer Roth-Gordon<br>
Associate Professor Emerita<br>
School of Anthropology<br>
University of Arizona<br>
Tucson, AZ 85721-0030<br>
<br>
<br>
<br>
________________________________<br>
From: Linganth <linganth-bounces@listserv.linguistlist.org> on behalf of Jocelyn Aznar <contact@jocelynaznar.eu><br>
Sent: Thursday, April 9, 2026 9:28 PM<br>
To: linganth@listserv.linguistlist.org <linganth@listserv.linguistlist.org><br>
Subject: [EXT] Re: [Linganth] Recommendations for tools transcribing and analyzing large amounts of data<br>
<br>
External Email<br>
<br>
Hi everyone,<br>
<br>
I'm curious, how do you end up with so much data without first thinking<br>
about how you will handle it?<br>
<br>
As you are within an English department, I assume you work with English?<br>
Do you have some budget? What kind of annotation do you need? which<br>
format? how do you do your analysis? using CSV files? XML? should the<br>
data be reusable by other researchers? meant for being archived? FAIR? etc.<br>
<br>
Using online AI tools is probably not ethical, as you have no way to<br>
know what will the companies do with the data and what the people you<br>
recorded said... If you have a recent computer, some budget or access to<br>
University servers, you can use for instance Whisper and a model from<br>
Mistral (like the 7B) to do some annotations automatically. With<br>
languages like English, French and co, it works quite well. But that<br>
requires some scripting.<br>
<br>
Best,<br>
Jocelyn<br>
<br>
Le 09/04/2026 ? 21:13, Nathan Straub ??? a ?crit :<br>
> Hi Dominika,<br>
><br>
> I use Vook.ai (an AI-based subscription service) for rapid automatic<br>
> transcription of English. (It also does Spanish, French, Italian,<br>
> Portuguese, and German.) You would likely have to sort out overlaps and<br>
> speaker labels on you own after that.<br>
><br>
> For field recordings, I liked using SIL's Saymore software, because it<br>
> provided a place to store recordings and break up a recording into short<br>
> breath groups and listen again and again with slow speech and type up<br>
> rough transcriptions, and then I could port the vernacular and free<br>
> translation lines into FLEx.<br>
><br>
> Which languages are you working with?<br>
><br>
> Nathan<br>
><br>
> We are sent into this world for some end.  It is our duty to discover by<br>
> close study what this end is & when we once discover it to pursue it<br>
> with unconquerable perseverance.<br>
> JQA at age 12 to his brother Charles (June 1778)<br>
><br>
> On Thu, Apr 9, 2026, 12:02 Dominika Baran, Ph.D.<br>
> <dominika.baran@duke.edu <<a href="mailto:dominika.baran@duke.edu" id="OWAcc2c7d5c-ab7a-b261-29d9-958332810213" class="OWAAutoLink">mailto:dominika.baran@duke.edu</a>>> wrote:<br>
><br>
> Dear Colleagues,<br>
><br>
> I am looking for recommendations of your favorite tool(s), at the<br>
> moment, for processing large amounts of recorded spoken & written<br>
> conversational data (informal interviews, free conversations), for<br>
> both transcription and coding & analysis.<br>
><br>
> I have about 100 hours of digitally recorded conversations,<br>
> including those among multiple speakers, with lots of simultaneous<br>
> speech, two conversations going on at once, overlap, and code-<br>
> switching (mostly bilingual, occasionally trilingual). I also have<br>
> 13 years of written group chat conversations, which don?t need<br>
> transcribing but it is over 300,000 words. I am looking for<br>
> suggestions for software, online or otherwise, for both<br>
> transcription (which is tricky because of the multilingual and<br>
> overlapping conversations) and, more importantly, organization,<br>
> coding, and analysis. It has been a while since I have dealt with<br>
> THIS much data and I am sure there is a lot out there that I don?t<br>
> know about - all and any suggestions of what has worked for folks<br>
> are very much appreciated!<br>
><br>
> Best,<br>
> Dominika<br>
><br>
><br>
> Dominika M. Baran<br>
><br>
> Associate Professor<br>
><br>
> English Department<br>
><br>
> Duke University<br>
><br>
> Allen Building 303<br>
><br>
> Durham, NC 27708<br>
><br>
> Pronouns: she/her/hers<br>
><br>
> _______________________________________________<br>
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End of Linganth Digest, Vol 139, Issue 13<br>
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