242:. Numerous applications are in development, with different institutions and companies taking various approaches to privacy and data collection. Current efforts are aimed at gathering data. In a later stage, it is possible that sound apps will have the capacity (and ethical approvals) to provide information back to users. In order to develop and train signal analysis approaches, large datasets are required.
117:
22:
63:
283:
by artificial intelligence to help in this scenario, by surveying which types of related or contextually significant phenomena can be automatically assessed from speech or sound has been recently overviewed. These include the automatic recognition and monitoring of breathing, dry and wet coughing or
287:
Additionally, the potential use-cases of intelligent speech analysis for COVID-19 diagnosed patients has also been presented. In particular, by analysing speech recordings from these patients, an audio-only-based model to automatically categorise the health state of patients from four aspects,
266:
which offer solutions for user tracking have been developed. At the same time a number of approaches which tries to use respiratory sounds and artificial intelligence to understand if the disease can be diagnosed have been proposed. A few studies are available as
749:
Brown, Chloe; Chauhan, Jagmohan; Grammenos, Andreas; Han, Jing; Hasthanasombat, Apinan; Spathis, Dimitris; Xia, Tong; Cicuta, Pietro; Mascolo, Cecilia (2020). "Exploring
Automatic Diagnosis of COVID-19 from Crowdsourced Respiratory Sound Data".
311:
A large-scale crowdsourced dataset of respiratory sounds has been collected to aid diagnosis of COVID-19: coughs and breathing sounds are sufficient to distinguish users affected by COVID-19 versus those affected by asthma or healthy controls.
291:
Machine learning methods have been explored to recognize and diagnose coughs from different diseases. These included a low complexity, automated recognition and diagnostic tool for screening respiratory infections that utilizes
315:
Behind these studies is the ambition that automated systems to screen for respiratory diseases based on voice, raw cough or other sound data would have positive medical applications in both clinical and public health arenas.
812:
656:
Schuller, Björn W.; Schuller, Dagmar M. (2020). "COVID-19 and
Computer Audition: An Overview on What Speech & Sound Analysis Could Contribute in the SARS-CoV-2 Corona Crisis".
450:
134:
35:
288:
including the severity of illness, sleep quality, fatigue, and anxiety, is constructed. This work shows promise in estimating the severity of illness.
677:
Han, Jing; Song, Meishu (2020). "An Early Study on
Intelligent Analysis of Speech under COVID-19: Severity, Sleep Quality, Fatigue, and Anxiety".
181:
725:
153:
41:
160:
595:
777:
218:
200:
49:
167:
138:
149:
807:
293:
423:
127:
382:
Pending legal advice. Hoping to be made available to researchers, subject to legal framework protecting privacy.
255:
174:
365:
259:
698:
Bales, Charles; Nabeel, Muhammad (2020). "Can
Machine Learning be Used to Recognize and Diagnose Coughs?".
535:
526:
92:
752:
Proceedings of the 26th ACM SIGKDD International
Conference on Knowledge Discovery & Data Mining
565:
617:
396:
73:
783:
755:
731:
703:
678:
657:
262:
techniques are being considered as tools in aiding our response to global health crisis. Other
773:
721:
258:
in March 2020 and has affected a growing number of people globally. In this context, advanced
251:
239:
296:(CNNs) to detect cough within environment audio and diagnose three potential illnesses (i.e.
765:
713:
539:
280:
801:
787:
735:
301:
263:
717:
116:
297:
235:
769:
305:
238:
designed to collect respiratory sounds and aid diagnosis in response to the
82:
284:
sneezing sounds, speech under cold, eating behaviour, sleepiness, or pain.
62:
268:
362:
Cough, breathing and voice + symptoms and elements of medical history.
760:
708:
683:
662:
700:
2020 International
Conference on e-Health and Bioengineering (EHB)
634:
110:
56:
15:
379:
English, German, French, Italian, Spanish, Greek, Portuguese
532:
390:
Audio data collection to establish diagnostic potential
359:
Audio data collection to establish diagnostic potential
582:
Audio data collection to establish screening potential
336:
Sponsor of project (University / Company / grassroots)
87:
77:
141:. Unsourced material may be challenged and removed.
373:Cambridge Univ. Computer Lab. Ethics Committee.
588:Wadhwani Institute for Artificial Intelligence
813:Software associated with the COVID-19 pandemic
333:Nature of Sounds recorded, and other metadata
308:) based on their unique cough audio features.
8:
50:Learn how and when to remove these messages
254:was announced as a global pandemic by the
759:
707:
682:
661:
345:Cumulative Samples Collected (with date)
219:Learn how and when to remove this message
201:Learn how and when to remove this message
451:École Polytechnique Fédérale de Lausanne
323:
271:(i.e. not yet peer-reviewed) documents.
648:
330:Functionality and aim/stage of project
320:List of apps to analyse COVID-19 sounds
559:Audio data collection, medical advice
393:Cough and elements of medical history
7:
594:State governments of Odisha, Bihar,
139:adding citations to reliable sources
596:Brihanmumbai Municipal Corporation
14:
471:Audio data collection, diagnosis
417:Audio data collection, diagnosis
150:"Apps to analyse COVID-19 sounds"
31:This article has multiple issues.
115:
61:
20:
635:https://github.com/virufy/covid
232:Apps to analyse COVID-19 sounds
126:needs additional citations for
39:or discuss these issues on the
1:
718:10.1109/EHB50910.2020.9280115
631:English, Spanish, Portuguese
294:convolutional neural networks
236:mobile software applications
474:Cough, breathing and voice
829:
424:Carnegie Mellon University
523:Cough, COVID-19 symptoms
281:speech and sound analysis
256:World Health Organization
279:The potential for using
770:10.1145/3394486.3412865
585:Cough, Voice, Symptoms
366:University of Cambridge
260:artificial intelligence
76:, as no other articles
754:. pp. 3474–3484.
611:Audio data collection
520:Audio data collection
495:Audio data collection
444:Audio data collection
556:COVID-19 Voice Study
533:https://coughmode.com
414:Covid Voice Detector
579:Cough Against Covid
545:Advarra Central IRB
387:Breathe for Science
356:COVID-19 Sounds App
135:improve this article
808:Mobile applications
618:Stanford University
397:New York University
623:Web, Android, iOS
538:2021-08-03 at the
370:Web, Android, iOS
95:for suggestions.
85:to this page from
727:978-1-7281-8803-4
640:
639:
342:Ethical approval
252:COVID-19 outbreak
240:COVID-19 pandemic
229:
228:
221:
211:
210:
203:
185:
109:
108:
54:
820:
792:
791:
763:
746:
740:
739:
711:
702:. pp. 1–4.
695:
689:
688:
686:
674:
668:
667:
665:
653:
527:Healthmode, Inc.
376:6000 (1 May 20)
324:
224:
217:
206:
199:
195:
192:
186:
184:
143:
119:
111:
104:
101:
90:
88:related articles
65:
57:
46:
24:
23:
16:
828:
827:
823:
822:
821:
819:
818:
817:
798:
797:
796:
795:
780:
748:
747:
743:
728:
697:
696:
692:
676:
675:
671:
655:
654:
650:
645:
540:Wayback Machine
508:489 (7 May 20)
322:
277:
248:
225:
214:
213:
212:
207:
196:
190:
187:
144:
142:
132:
120:
105:
99:
96:
86:
83:introduce links
66:
25:
21:
12:
11:
5:
826:
824:
816:
815:
810:
800:
799:
794:
793:
778:
741:
726:
690:
669:
647:
646:
644:
641:
638:
637:
632:
629:
626:
624:
621:
615:
612:
609:
605:
604:
602:
600:
598:
592:
589:
586:
583:
580:
576:
575:
573:
571:
568:
566:Vocalis Health
563:
560:
557:
553:
552:
550:
548:
546:
543:
529:
524:
521:
518:
514:
513:
511:
509:
506:
504:
501:
499:
496:
493:
489:
488:
486:
484:
482:
480:
477:
475:
472:
469:
465:
464:
462:
460:
458:
456:
453:
448:
445:
442:
438:
437:
435:
433:
431:
429:
426:
421:
418:
415:
411:
410:
408:
406:
404:
402:
399:
394:
391:
388:
384:
383:
380:
377:
374:
371:
368:
363:
360:
357:
353:
352:
349:
346:
343:
340:
337:
334:
331:
328:
321:
318:
276:
273:
247:
244:
227:
226:
209:
208:
191:September 2020
123:
121:
114:
107:
106:
93:Find link tool
69:
67:
60:
55:
29:
28:
26:
19:
13:
10:
9:
6:
4:
3:
2:
825:
814:
811:
809:
806:
805:
803:
789:
785:
781:
779:9781450379984
775:
771:
767:
762:
757:
753:
745:
742:
737:
733:
729:
723:
719:
715:
710:
705:
701:
694:
691:
685:
680:
673:
670:
664:
659:
652:
649:
642:
636:
633:
630:
627:
625:
622:
620:(unofficial)
619:
616:
614:Cough, voice
613:
610:
607:
606:
603:
601:
599:
597:
593:
590:
587:
584:
581:
578:
577:
574:
572:
569:
567:
564:
561:
558:
555:
554:
551:
549:
547:
544:
541:
537:
534:
530:
528:
525:
522:
519:
516:
515:
512:
510:
507:
505:
502:
500:
497:
494:
491:
490:
487:
485:
483:
481:
478:
476:
473:
470:
467:
466:
463:
461:
459:
457:
455:Web, Android
454:
452:
449:
446:
443:
440:
439:
436:
434:
432:
430:
427:
425:
422:
419:
416:
413:
412:
409:
407:
405:
403:
400:
398:
395:
392:
389:
386:
385:
381:
378:
375:
372:
369:
367:
364:
361:
358:
355:
354:
351:Data Release
350:
347:
344:
341:
338:
335:
332:
329:
326:
325:
319:
317:
313:
309:
307:
303:
302:bronchiolitis
299:
295:
289:
285:
282:
275:Methodologies
274:
272:
270:
265:
264:COVID-19 apps
261:
257:
253:
245:
243:
241:
237:
233:
223:
220:
205:
202:
194:
183:
180:
176:
173:
169:
166:
162:
159:
155:
152: –
151:
147:
146:Find sources:
140:
136:
130:
129:
124:This article
122:
118:
113:
112:
103:
94:
89:
84:
80:
79:
75:
70:This article
68:
64:
59:
58:
53:
51:
44:
43:
38:
37:
32:
27:
18:
17:
751:
744:
699:
693:
672:
651:
314:
310:
290:
286:
278:
249:
231:
230:
215:
197:
188:
178:
171:
164:
157:
145:
133:Please help
128:verification
125:
97:
71:
47:
40:
34:
33:Please help
30:
802:Categories
761:2006.05919
709:2004.01495
684:2005.00096
663:2003.11117
643:References
531:Web, iOS (
517:Coughmode
492:Detectnow
348:Languages
339:Platforms
298:bronchitis
161:newspapers
91:; try the
78:link to it
36:improve it
788:219558912
736:214795228
468:VoiceMed
441:Coughvid
306:pertussis
269:preprints
100:June 2022
81:. Please
42:talk page
536:Archived
608:Virufy
246:History
175:scholar
786:
776:
734:
724:
562:Voice
498:Cough
447:Cough
420:Voice
177:
170:
163:
156:
148:
74:orphan
72:is an
784:S2CID
756:arXiv
732:S2CID
704:arXiv
679:arXiv
658:arXiv
628:5000
327:Name
182:JSTOR
168:books
774:ISBN
722:ISBN
591:Web
570:Web
503:Web
479:Web
428:Web
401:Web
304:and
250:The
234:are
154:news
766:doi
714:doi
137:by
804::
782:.
772:.
764:.
730:.
720:.
712:.
542:)
300:,
45:.
790:.
768::
758::
738:.
716::
706::
687:.
681::
666:.
660::
222:)
216:(
204:)
198:(
193:)
189:(
179:·
172:·
165:·
158:·
131:.
102:)
98:(
52:)
48:(
Text is available under the Creative Commons Attribution-ShareAlike License. Additional terms may apply.
