import{s as Q,n as Y,o as Z}from"../chunks/scheduler.cd324960.js";import{S as ee,i as te,e as l,s as i,c as U,h as ae,a as r,d as a,b as o,f as J,g as G,j as b,k as K,l as ne,m as n,n as R,t as j,o as B,p as I}from"../chunks/index.d5c3adcc.js";import{C as ie,H as oe,E as le}from"../chunks/MermaidChart.svelte_svelte_type_style_lang.481f2bec.js";function re(N){let s,_,x,$,p,y,c,k,d,W=`This Unit pieced together many components from previous units, introducing the tasks of speech-to-speech translation,
voice assistants and speaker diarization. The supplemental reading material is thus split into these three new tasks
for your convenience:`,C,u,q="Speech-to-speech translation:",S,m,O='<li><a href="https://ai.facebook.com/blog/advancing-direct-speech-to-speech-modeling-with-discrete-units/" rel="nofollow">STST with discrete units</a> by Meta AI: a direct approach to STST through encoder-decoder models</li> <li><a href="https://ai.facebook.com/blog/ai-translation-hokkien/" rel="nofollow">Hokkien direct speech-to-speech translation</a> by Meta AI: a direct approach to STST using encoder-decoder models with a two-stage decoder</li> <li><a href="https://arxiv.org/abs/2203.13339" rel="nofollow">Leveraging unsupervised and weakly-supervised data to improve direct STST</a> by Google: proposes new approaches for leveraging unsupervised and weakly supervised data for training direct STST models and a small change to the Transformer architecture</li> <li><a href="https://google-research.github.io/lingvo-lab/translatotron2/" rel="nofollow">Translatotron-2</a> by Google: a system that is able to retain speaker characteristics in translated speech</li>',M,h,V="Voice Assistant:",L,f,X='<li><a href="https://www.amazon.science/publications/accurate-detection-of-wake-word-start-and-end-using-a-cnn" rel="nofollow">Accurate wakeword detection</a> by Amazon: a low latency approach for wakeword detection for on-device applications</li> <li><a href="https://arxiv.org/pdf/1811.06621.pdf" rel="nofollow">RNN-Transducer Architecture</a> by Google: a modification to the CTC architecture for streaming on-device ASR</li>',z,g,D="Meeting Transcriptions:",H,v,F='<li><a href="https://huggingface.co/pyannote/speaker-diarization/blob/main/technical_report_2.1.pdf" rel="nofollow">pyannote.audio Technical Report</a> by Hervé Bredin: this report describes the main principles behind the <code>pyannote.audio</code> speaker diarization pipeline</li> <li><a href="https://arxiv.org/pdf/2303.00747.pdf" rel="nofollow">Whisper X</a> by Max Bain et al.: a superior approach to computing word-level timestamps using the Whisper model</li>',P,w,A,T,E;return p=new ie({props:{containerStyle:"float: right; margin-left: 10px; display: inline-flex; position: relative; z-index: 10;"}}),c=new oe({props:{title:"Supplemental reading and resources",local:"supplemental-reading-and-resources",headingTag:"h1"}}),w=new le({props:{source:"https://github.com/huggingface/audio-transformers-course/blob/main/chapters/en/chapter7/supplemental_reading.mdx"}}),{c(){s=l("meta"),_=i(),x=l("p"),$=i(),U(p.$$.fragment),y=i(),U(c.$$.fragment),k=i(),d=l("p"),d.textContent=W,C=i(),u=l("p"),u.textContent=q,S=i(),m=l("ul"),m.innerHTML=O,M=i(),h=l("p"),h.textContent=V,L=i(),f=l("ul"),f.innerHTML=X,z=i(),g=l("p"),g.textContent=D,H=i(),v=l("ul"),v.innerHTML=F,P=i(),U(w.$$.fragment),A=i(),T=l("p"),this.h()},l(e){const t=ae("svelte-u9bgzb",document.head);s=r(t,"META",{name:!0,content:!0}),t.forEach(a),_=o(e),x=r(e,"P",{}),J(x).forEach(a),$=o(e),G(p.$$.fragment,e),y=o(e),G(c.$$.fragment,e),k=o(e),d=r(e,"P",{"data-svelte-h":!0}),b(d)!=="svelte-1iump5g"&&(d.textContent=W),C=o(e),u=r(e,"P",{"data-svelte-h":!0}),b(u)!=="svelte-pe80dk"&&(u.textContent=q),S=o(e),m=r(e,"UL",{"data-svelte-h":!0}),b(m)!=="svelte-14xetpv"&&(m.innerHTML=O),M=o(e),h=r(e,"P",{"data-svelte-h":!0}),b(h)!=="svelte-1s9n18"&&(h.textContent=V),L=o(e),f=r(e,"UL",{"data-svelte-h":!0}),b(f)!=="svelte-zlamoz"&&(f.innerHTML=X),z=o(e),g=r(e,"P",{"data-svelte-h":!0}),b(g)!=="svelte-7hkdj4"&&(g.textContent=D),H=o(e),v=r(e,"UL",{"data-svelte-h":!0}),b(v)!=="svelte-apznjz"&&(v.innerHTML=F),P=o(e),G(w.$$.fragment,e),A=o(e),T=r(e,"P",{}),J(T).forEach(a),this.h()},h(){K(s,"name","hf:doc:metadata"),K(s,"content",se)},m(e,t){ne(document.head,s),n(e,_,t),n(e,x,t),n(e,$,t),R(p,e,t),n(e,y,t),R(c,e,t),n(e,k,t),n(e,d,t),n(e,C,t),n(e,u,t),n(e,S,t),n(e,m,t),n(e,M,t),n(e,h,t),n(e,L,t),n(e,f,t),n(e,z,t),n(e,g,t),n(e,H,t),n(e,v,t),n(e,P,t),R(w,e,t),n(e,A,t),n(e,T,t),E=!0},p:Y,i(e){E||(j(p.$$.fragment,e),j(c.$$.fragment,e),j(w.$$.fragment,e),E=!0)},o(e){B(p.$$.fragment,e),B(c.$$.fragment,e),B(w.$$.fragment,e),E=!1},d(e){e&&(a(_),a(x),a($),a(y),a(k),a(d),a(C),a(u),a(S),a(m),a(M),a(h),a(L),a(f),a(z),a(g),a(H),a(v),a(P),a(A),a(T)),a(s),I(p,e),I(c,e),I(w,e)}}}const se='{"title":"Supplemental reading and resources","local":"supplemental-reading-and-resources","sections":[],"depth":1}';function pe(N){return Z(()=>{new URLSearchParams(window.location.search).get("fw")}),[]}class me extends ee{constructor(s){super(),te(this,s,pe,re,Q,{})}}export{me as component};
