Access to recorded interviews: A research agenda

Recorded interviews form a rich basis for scholarly inquiry. Examples include oral histories, community memory projects, and interviews conducted for broadcast media. Emerging technologies offer the potential to radically transform the way in which recorded interviews are made accessible, but this vision will demand substantial investments from a broad range of research communities. This article reviews the present state of practice for making recorded interviews available and the state-of-the-art for key component technologies. A large number of important research issues are identified, and from that set of issues, a coherent research agenda is proposed

Radio Oranje: Enhanced Access to a Historical Spoken Word Collection

Access to historical audio collections is typically very restricted:\ud content is often only available on physical (analog) media and the\ud metadata is usually limited to keywords, giving access at the level\ud of relatively large fragments, e.g., an entire tape. Many spoken\ud word heritage collections are now being digitized, which allows the\ud introduction of more advanced search technology. This paper presents\ud an approach that supports online access and search for recordings of\ud historical speeches. A demonstrator has been built, based on the\ud so-called Radio Oranje collection, which contains radio speeches by\ud the Dutch Queen Wilhelmina that were broadcast during World War II.\ud The audio has been aligned with its original 1940s manual\ud transcriptions to create a time-stamped index that enables the speeches to be\ud searched at the word level. Results are presented together with\ud related photos from an external database

Using term clouds to represent segment-level semantic content of podcasts

Spoken audio, like any time-continuous medium, is notoriously difficult to browse or skim without support of an interface providing semantically annotated jump points to signal the user where to listen in. Creation of time-aligned metadata by human annotators is prohibitively expensive, motivating the investigation of representations of segment-level semantic content based on transcripts generated by automatic speech recognition (ASR). This paper examines the feasibility of using term clouds to provide users with a structured representation of the semantic content of podcast episodes. Podcast episodes are visualized as a series of sub-episode segments, each represented by a term cloud derived from a transcript generated by automatic speech recognition (ASR). Quality of segment-level term clouds is measured quantitatively and their utility is investigated using a small-scale user study based on human labeled segment boundaries. Since the segment-level clouds generated from ASR-transcripts prove useful, we examine an adaptation of text tiling techniques to speech in order to be able to generate segments as part of a completely automated indexing and structuring system for browsing of spoken audio. Results demonstrate that the segments generated are comparable with human selected segment boundaries

Audiovisual Media Annotation Using Qualitative Data Analysis Software: A Comparative Analysis

The variety of specialized tools designed to facilitate analysis of audio-visual (AV) media are useful not only to media scholars and oral historians but to other researchers as well. Both Qualitative Data Analysis Software (QDAS) packages and dedicated systems created for specific disciplines, such as linguistics, can be used for this purpose. Software proliferation challenges researchers to make informed choices about which package will be most useful for their project. This paper aims to present an information science perspective of the scholarly use of tools in qualitative research of audio-visual sources. It provides a baseline of affordances based on functionalities with the goal of making the types of research tasks that they support more explicit (e.g., transcribing, segmenting, coding, linking, and commenting on data). We look closely at how these functionalities relate to each other, and at how system design influences research tasks

Speech and language processes in children who stutter compared to those who do not within an oral narrative task

Background and Purpose: Language ability in children who stutter has been linked to the occurrence of stuttering, however, the validity of research supporting this connection has been recently questioned. Previous research, within this area, has been limited by methodological confounds, such as lack of appropriately matched comparison groups, and the use of measures with insufficient sensitivity to potentially examine the subtle differences between children who stutter (CWS) and children who do not stutter (CWNS). Frequent hesitations or pauses are defining characteristics of the speech of people who stutter. However, little is known about the nature and frequency of the pauses found within the speech of CWS. Examination of pauses within speech is a novel method of analysing speech production with the potential to provide insight into the speech and language processing and an opportunity to explore differences between normal and disordered speech. This study aimed to compare the speech and language processes of CWS to CWNS. Methods and Procedures: This study compared language and pause measures taken from narrative samples of age (Mean age = 6 years and 10 months) and gender matched CWS (n= 6), and CWNS (n= 6). The oral narratives were collected using a story generation task and were transcribed and analysed using the Systematic Analysis of Language Transcription (SALT) (Miller & Iglesias, 2012). For each sample the mean length of utterance in morphemes, the total number of utterances, the number of different word roots, the % intelligible words and the % words in mazes were calculated. Additionally the computer software programme PRAAT was used to segment the samples into sections of speech and pauses and the segmented samples were transformed into two lognormal pause distributions (Boersma, & Weenink, 2013). The pauses of CWS were analysed twice, once with stutters present and once with stutters removed. For the two groups the results from the language and pause analyses were compared through ttests and the relationship between Percent Syllables stutters, and the pause and language measures, was examined through correlation. Results: For all discourse and pause measures the difference between the CWS and CWNS was not significant. The only significant difference was found between the CWS and CWNS in the degree of overlap of the short and long pause distributions (Misclassification Rate) in the samples of CWS, when stutters were present. Percent Syllables Stuttered was found to be significantly positively correlated with Percent Mazes and Syllables Spoken per Second when stutters were present in the samples of CWS. Percent Syllables Stuttered was found to be significantly negatively correlated with Short Pause Mean with stutters present in the samples of CWS. Conclusions: In this study, the connection between stuttering and language was not supported as the language measures gathered from CWS were all found to be similar to those gathered from CWNS. The findings in this research support explanations of stuttering in which stuttering is attributed to factors exclusive to language ability, such as stuttering being a difficulty in speech motor contro