The impact of brand and product placements in electronic games

In an environment where it has become increasingly difficult to attract consumer attention, marketers have begun to explore alternative forms of marketing communication. One such form that has emerged is product placement, which has more recently appeared in electronic games. Given changes in media consumption and the growth of the games industry, it is not surprising that games are being exploited as a medium for promotional content. Other market developments are also facilitating and encouraging their use, in terms of both the insertion of brand messages into video games and the creation of brand-centred environments, labelled ‘advergames’. However, while there is much speculation concerning the beneficial outcomes for marketers, there remains a lack of academic work in this area and little empirical evidence of the actual effects of this form of promotion on game players. Only a handful of studies are evident in the literature, which have explored the influence of game placements on consumers. The majority have studied their effect on brand awareness, largely demonstrating that players can recall placed brands. Further, most research conducted to date has focused on computer and online games, but consoles represent the dominant platform for play (Taub, 2004). Finally, advergames have largely been neglected, particularly those in a console format. Widening the gap in the literature is the fact that insufficient academic attention has been given to product placement as a marketing communication strategy overall, and to games in general. The unique nature of the strategy also makes it difficult to apply existing literature to this context. To address a significant need for information in both the academic and business domains, the current research investigates the effects of brand and product placements in video games and advergames on consumer attitude to the brand and corporate image. It was conducted in two stages. Stage one represents a pilot study. It explored the effects of use simulated and peripheral placements in video games on players’ and observers’ attitudinal responses, and whether these are influenced by involvement with a product category or skill level in the game. The ability of gamers to recall placed brands was also examined. A laboratory experiment was employed with a small sample of sixty adult subjects drawn from an Australian east-coast university, some of who were exposed to a console video game on a television set. The major finding of study one is that placements in a video game have no effect on gamers’ attitudes, but they are recalled. For stage two of the research, a field experiment was conducted with a large, random sample of 350 student respondents to investigate the effects on players of brand and product placements in handheld video games and advergames. The constructs of brand attitude and corporate image were again tested, along with several potential confounds. Consistent with the pilot, the results demonstrate that product placement in electronic games has no effect on players’ brand attitudes or corporate image, even when allowing for their involvement with the product category, skill level in the game, or skill level in relation to the medium. Age and gender also have no impact. However, the more interactive a player perceives the game to be, the higher their attitude to the placed brand and corporate image of the brand manufacturer. In other words, when controlling for perceived interactivity, players experienced more favourable attitudes, but the effect was so weak it probably lacks practical significance. It is suggested that this result can be explained by the existence of excitation transfer, rather than any processing of placed brands. The current research provides strong, empirical evidence that brand and product placements in games do not produce strong attitudinal responses. It appears that the nature of the game medium, game playing experience and product placement impose constraints on gamer motivation, opportunity and ability to process these messages, thereby precluding their impact on attitude to the brand and corporate image. Since this is the first study to investigate the ability of video game and advergame placements to facilitate these deeper consumer responses, further research across different contexts is warranted. Nevertheless, the findings have important theoretical and managerial implications. This investigation makes a number of valuable contributions. First, it is relevant to current marketing practice and presents findings that can help guide promotional strategy decisions. It also presents a comprehensive review of the games industry and associated activities in the marketplace, relevant for marketing practitioners. Theoretically, it contributes new knowledge concerning product placement, including how it should be defined, its classification within the existing communications framework, its dimensions and effects. This is extended to include brand-centred entertainment. The thesis also presents the most comprehensive analysis available in the literature of how placements appear in games. In the consumer behaviour discipline, the research builds on theory concerning attitude formation, through application of MacInnis and Jaworski’s (1989) Integrative Attitude Formation Model. With regards to the games literature, the thesis provides a structured framework for the comparison of games with different media types; it advances understanding of the game medium, its characteristics and the game playing experience; and provides insight into console and handheld games specifically, as well as interactive environments generally. This study is the first to test the effects of interactivity in a game environment, and presents a modified scale that can be used as part of future research. Methodologically, it addresses the limitations of prior research through execution of a field experiment and observation with a large sample, making this the largest study of product placement in games available in the literature. Finally, the current thesis offers comprehensive recommendations that will provide structure and direction for future study in this important field.

Acoustic keyword spotting in speech with applications to data mining

Keyword Spotting is the task of detecting keywords of interest within continu- ous speech. The applications of this technology range from call centre dialogue systems to covert speech surveillance devices. Keyword spotting is particularly well suited to data mining tasks such as real-time keyword monitoring and unre- stricted vocabulary audio document indexing. However, to date, many keyword spotting approaches have su®ered from poor detection rates, high false alarm rates, or slow execution times, thus reducing their commercial viability. This work investigates the application of keyword spotting to data mining tasks. The thesis makes a number of major contributions to the ¯eld of keyword spotting. The ¯rst major contribution is the development of a novel keyword veri¯cation method named Cohort Word Veri¯cation. This method combines high level lin- guistic information with cohort-based veri¯cation techniques to obtain dramatic improvements in veri¯cation performance, in particular for the problematic short duration target word class. The second major contribution is the development of a novel audio document indexing technique named Dynamic Match Lattice Spotting. This technique aug- ments lattice-based audio indexing principles with dynamic sequence matching techniques to provide robustness to erroneous lattice realisations. The resulting algorithm obtains signi¯cant improvement in detection rate over lattice-based audio document indexing while still maintaining extremely fast search speeds. The third major contribution is the study of multiple veri¯er fusion for the task of keyword veri¯cation. The reported experiments demonstrate that substantial improvements in veri¯cation performance can be obtained through the fusion of multiple keyword veri¯ers. The research focuses on combinations of speech background model based veri¯ers and cohort word veri¯ers. The ¯nal major contribution is a comprehensive study of the e®ects of limited training data for keyword spotting. This study is performed with consideration as to how these e®ects impact the immediate development and deployment of speech technologies for non-English languages.

Automatic spoken language identification utilizing acoustic and phonetic speech information

Automatic spoken Language Identi¯cation (LID) is the process of identifying the language spoken within an utterance. The challenge that this task presents is that no prior information is available indicating the content of the utterance or the identity of the speaker. The trend of globalization and the pervasive popularity of the Internet will amplify the need for the capabilities spoken language identi¯ca- tion systems provide. A prominent application arises in call centers dealing with speakers speaking di®erent languages. Another important application is to index or search huge speech data archives and corpora that contain multiple languages. The aim of this research is to develop techniques targeted at producing a fast and more accurate automatic spoken LID system compared to the previous National Institute of Standards and Technology (NIST) Language Recognition Evaluation. Acoustic and phonetic speech information are targeted as the most suitable fea- tures for representing the characteristics of a language. To model the acoustic speech features a Gaussian Mixture Model based approach is employed. Pho- netic speech information is extracted using existing speech recognition technol- ogy. Various techniques to improve LID accuracy are also studied. One approach examined is the employment of Vocal Tract Length Normalization to reduce the speech variation caused by di®erent speakers. A linear data fusion technique is adopted to combine the various aspects of information extracted from speech. As a result of this research, a LID system was implemented and presented for evaluation in the 2003 Language Recognition Evaluation conducted by the NIST.

The use of phase in complex spectrum subtraction for robust speech recognition

In this paper we propose a new method for utilising phase information by complementing it with traditional magnitude-only spectral subtraction speech enhancement through Complex Spectrum Subtraction (CSS). The proposed approach has the following advantages over traditional magnitude-only spectral subtraction: (a) it introduces complementary information to the enhancement algorithm; (b) it reduces the total number of algorithmic parameters, and; (c) is designed for improving clean speech magnitude spectra and is therefore suitable for both automatic speech recognition (ASR) and speech perception applications. Oracle-based ASR experiments verify this approach, showing an average of 20% relative word accuracy improvements when accurate estimates of the phase spectrum are available. Based on sinusoidal analysis and assuming stationarity between observations (which is shown to be better approximated as the frame rate is increased), this paper also proposes a novel method for acquiring the phase information called Phase Estimation via Delay Projection (PEDEP). Further oracle ASR experiments validate the potential for the proposed PEDEP technique in ideal conditions. Realistic implementation of CSS with PEDEP shows performance comparable to state of the art spectral subtraction techniques in a range of 15-20 dB signal-to-noise ratio environments. These results clearly demonstrate the potential for using phase spectra in spectral subtractive enhancement applications, and at the same time highlight the need for deriving more accurate phase estimates in a wider range of noise conditions.

Microphone array beamforming approach to blind speech separation

In this paper, we present a microphone array beamforming approach to blind speech separation. Unlike previous beamforming approaches, our system does not require a-priori knowledge of the microphone placement and speaker location, making the system directly comparable other blind source separation methods which require no prior knowledge of recording conditions. Microphone location is automatically estimated using an assumed noise field model, and speaker locations are estimated using cross correlation based methods. The system is evaluated on the data provided for the PASCAL Speech Separation Challenge 2 (SSC2), achieving a word error rate of 58% on the evaluation set.