The vocalisations of animals are results of particular emotional states. For example, the stress screams of pigs may be indicators of disturbed welfare. Our objective was to develop a system to monitor and record levels of stress calls in pigs, which could be employed in environments of breeding, transportation and slaughter. Using a combination of sound analysis by linear prediction coding and artificial neural networks, it was possible to detect the stress vocalisations of pigs in noisy pig units with few recognition errors (<5%). The system (STREMODO: stress monitor and documentation unit) running on PCs is insensitive to environmental noise, human speech and pig vocalisations other than screams. As a stand-alone device it can be routinely used for the objective, non-invasive measurement of acute stress in various farming environments. The system delivers reliable, reproducible registrations of stress vocalisations. Its detection quality in commercial systems was found to correlate well with that of human experts. STREMODO is particularly well-suited for comparisons of housing and management regimes. Since the system can be trained to recognise various animal vocalisations, its use with other species is also well within its scope.

A welfare audit that utilises numerically scored, animal-based outcome measures has been used successfully by McDonald's and other restaurant companies for over ten years. In 2010, audit data from two restaurant companies indicated that all 30 of their North American plants rendered 95% or more of the cattle insensible with a single shot from a captive-bolt gun. Eight pork plants that used electrical stunning placed the tongs correctly on 99% or more of the pigs. All animals were insensible prior to hoisting. In 32 beef plants, the percentage of cattle vocalising in the stunning area was 5% or less. In 94% of the beef plants and 86% of the pork plants, none of the animals fell during handling. The worst falling score was 2% in two of the plants. High standards were attained by making simple changes. To improve welfare, plant managers did the following: improved stunner maintenance; installed non-slip floors in stun boxes and unloading ramps; and trained employees. To reduce balking and improve animal movement, the following modifications were made: illumination of dark race entrances; moving of lamps to eliminate reflections; reducing equipment noise; stopping employee yelling; installation of solid sides on races or shields to prevent animals from seeing activity outside the facility; and the elimination of air blowing in the faces of approaching animals. Employees were trained to use behavioural principles of animal handling such as the point of balance and the flight zone. The five numerically scored outcome measures in this audit are critical control points that can detect a variety of problems. They are: i) the percentage of animals stunned effectively with a single application of the stunner; ii) the percentage of animals falling during handling must be 1% or less to pass; iii) the percentage of pigs or cattle vocalising (moo, bellow, squeal) in the stun box or while entering into the stun box must be 5% or less to pass (vocalisation scoring is not used for sheep); iv) the percentage of animals moved with an electric goad; and v) the percentage of animals rendered insensible before hoisting must be 100% to pass an audit. An animal is scored as either silent or as a vocaliser and whether stunned correctly with a single application or not stunned correctly. The audit also contains a list of banned practices that will result in an automatic failure. To maintain improvements in handling, 23 plants have installed video cameras that are monitored by auditors viewing the footage over the internet. These external auditors perform numerical scoring at random times throughout the day. Video auditing over the internet is an important new tool for improving welfare.

The lateral approximant in General British English (GB) is realised as light when occurring in the onset (leaf), and as dark in the rhyme (help, feel, google). Non-prevocalic positions are typical contexts for lenition, analysed in Element Theory as decomposition in weak positions. However, it is unclear how velarisation can be characterised as element loss if light [l] is represented as |A I|, while dark [ɫ] is represented as |A U|. Therefore, I propose that laterals in GB contain both the coronal |I| and the velar |U| element underlyingly (in addition to |A|), but because these cannot combine in a compound segment in English, they are both floating. Their association at the phrase level is determined by the apophonic chain (Guerssel & Lowenstamm 1996), mapped onto the structure of the syllable: |I| is attracted to the prevocalic position, |A| to the vocalic position and |U| to the postvocalic position. Darkening thus does not involve lenition of /l/, but partial interpretation in all positions. In contrast, I analyse vocalisation of dark [ɫ] as lenition, involving loss of |A| in weak positions. I integrate the lateral into the system of glides in English, and establish a typology of its behaviour across different accents.

Oestrus detection remains a problem in the dairy cattle industry. Therefore, automatic detection systems have been developed to detect specific behavioural changes at oestrus. Vocal behaviour has not been considered in such automatic oestrus detection systems in cattle, though the vocalisation rate is known to increase during oestrus. The main challenge in using vocalisation to detect oestrus is correctly identifying the calling individual when animals are moving freely in large groups, as oestrus needs to be detected at an individual level. Therefore, we aimed to automate vocalisation recording and caller identification in group-housed dairy cows. This paper first presents the details of such a system and then presents the results of a pilot study validating its functionality, in which the automatic detection of calls from individual heifers was compared to video-based assessment of these calls by a trained human observer, a technique that has, until now, been considered the ‘gold standard’. We developed a collar-based cattle call monitor (CCM) with structure-borne and airborne sound microphones and a recording unit and developed a postprocessing algorithm to identify the caller by matching the information from both microphones. Five group-housed heifers, each in the perioestrus or oestrus period, were equipped with a CCM prototype for 5 days. The recorded audio data were subsequently analysed and compared with audiovisual recordings. Overall, 1404 vocalisations from the focus heifers and 721 vocalisations from group mates were obtained. Vocalisations during collar changes or malfunctions of the CCM were omitted from the evaluation. The results showed that the CCM had a sensitivity of 87% and a specificity of 94%. The negative and positive predictive values were 80% and 96%, respectively. These results show that the detection of individual vocalisations and the correct identification of callers are possible, even in freely moving group-housed cattle. The results are promising for the future use of vocalisation in automatic oestrus detection systems.

Arbib offers a coherent proposal of how the brain has evolved to become language-capable. Integral to the argument are mirror neurons, cells discovered in macaque brains with interesting firing patterns, and studies on gestural communication of great apes. Here, I first discuss some complexities of the recent mirror neuron literature, which suggest that ‘mirroring’ may be an ontogenetically acquired, not an evolved, feature of neurons. Second, it is now clear that chimpanzee vocal behaviour is strongly mediated by social variables, and that individuals can use vocalisations to persuade and inform others, facts that have implications for gestural theories of language evolution. I conclude with discussing research most needed for making progress in understanding how human language has evolved.

Unlike the great apes and most other primates, all species of gibbons are known to produce elaborate, species-specific and sex-specific patterns of vocalisation usually referred to as “songs”. In most, but not all, species, mated pairs may characteristically combine their songs in a relatively rigid pattern to produce coordinated duet songs. Previous studies disagree on whether duetting or the absence of duetting represented the primitive condition in gibbons. The present study compares singing behaviour in all gibbon species. Various vocal characteristics were subjected to a phylogenetic analysis using previously published phylogenetic trees of the gibbon radiation as a framework. Variables included the degree of sex-specificity of the vocal repertoire, the occurrence of solo songs, and the preference for a specific time of day for song-production. The results suggest the following scenario for the evolution of gibbon songs: (1) The last common ancestor of recent gibbons produced duet songs. (2) Gibbon duets probably evolved from a song which was common to both sexes and which only later became separated into male-specific and female-specific parts (song-splitting theory). (3) A process tentatively called “duet-splitting” is suggested to have led secondarily from a duetting species to a non-duetting species, in that the contributions of the pair-partners split into temporally segregated solo songs. This appears to be the first time that a non-duetting animal can be shown to be derived from a duetting form. (4) The return to exclusive solo singing may be related to the isolated island distribution of the non-duetting species.